Islam West Africa Collection (IWAC)
REMOTE · ISLAM.ZMO.DE · 3 COMPONENTS
Read-only access to the Islam West Africa Collection via Hugging Face datasets.
Last scanned (17 hours ago)
Scores higher than 94% of remote servers
Reachable. Last reached 4 Nov 2026.
Category Education and Research
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →
Endpoint Security80
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one. See how to fix → View diagnostics → Partial
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- The HSTS (Strict-Transport-Security) header is present. View diagnostics → Pass
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability77
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 8501 tokens (~160/item across 53 items; 39 tools + 14 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management97
- Stability observed for 29 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage92
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 70% of tool parameters carry a description.Partial
- Structured output schemas are declared (41% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 39 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 41 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
- Supports UI / widget rendering.Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Nov 26 0
- Stability: pass → 0.97 functional
- 2 Nov 26 0
- Tool “search_by_sentiment” rewrote its description, which is the text the model reads security
- Tool “get_country_comparison” rewrote its description, which is the text the model reads security
- Server version: 5.0.0 → 6.0.0 functional
- “get_sentiment_distribution” reworded the description of “model” cosmetic
- “get_semantic_map” reworded the description of “color_by” cosmetic
- 30 Oct 26 0
- The server rewrote its instructions, which are the text every model session reads security
- Tool “search_references” rewrote its description, which is the text the model reads security
- Schema quality: excellent → good functional
- Server version: 4.3.1 → 5.0.0 functional
- “explore_corpus” added an optional parameter “link” cosmetic
- “get_topic_distribution” reworded the description of “keyword_mode” cosmetic
- “search_articles” reworded the description of “keyword” cosmetic
- “search_articles” reworded the description of “keyword_mode” cosmetic
- “search_audiovisual” reworded the description of “keyword” cosmetic
- “search_documents” reworded the description of “keyword” cosmetic
- “search_images” reworded the description of “keyword” cosmetic
- “search_index” reworded the description of “keyword” cosmetic
- “search_publications” reworded the description of “keyword” cosmetic
- “search_publications” reworded the description of “keyword_mode” cosmetic
- “search_references” reworded the description of “keyword” cosmetic
- “get_cooccurrence” reworded the description of “keyword_mode” cosmetic
- “get_field_distribution” reworded the description of “keyword_mode” cosmetic
- “get_lexical_metrics” reworded the description of “keyword_mode” cosmetic
- “get_place_distribution” reworded the description of “keyword_mode” cosmetic
- “get_semantic_map” reworded the description of “keyword_mode” cosmetic
- “get_sentiment_distribution” reworded the description of “keyword_mode” cosmetic
- “get_temporal_distribution” reworded the description of “keyword_mode” cosmetic
- 28 Oct 26 0
- Tool “explore_corpus” rewrote its description, which is the text the model reads security
- Server version: 4.2.0 → 4.3.1 functional
- 26 Oct 26 0
- Tool “list_locations” rewrote its description, which is the text the model reads security
- Tool “list_persons” rewrote its description, which is the text the model reads security
- Resource “skill-iwac-mcp-references/tools-by-phase.md” was removed ▼ functional
- Resource “skill-iwac-mcp-references/capabilities-overview.md” was removed ▼ functional
- Resource “skill-iwac-mcp-references/research-domains.md” was removed ▼ functional
- Resource “skill-iwac-mcp” was removed ▼ functional
- Resource “skill-iwac-mcp-SKILL.md” was removed ▼ functional
- Resource “skill-iwac-mcp-references/biases-and-limitations.md” was removed ▼ functional
- New resource “iwac-mcp” functional
- New resource “iwac-mcp/references/biases-and-limitations.md” functional
- New resource “iwac-mcp/references/capabilities-overview.md” functional
- New resource “iwac-mcp/references/research-domains.md” functional
- New resource “iwac-mcp/references/tools-by-phase.md” functional
- Server version: 4.1.0 → 4.2.0 functional
- 19 Oct 26 −1
- The server rewrote its instructions, which are the text every model session reads security
- Tool “get_similar_items” rewrote its description, which is the text the model reads security
- Tool coverage: 46% → 41% ▼ functional
- Server version: 3.9.0 → 4.1.0 functional
- New tool “semantic_search_references” functional
- New tool “semantic_search_articles” functional
- New tool “semantic_search_images” functional
- New tool “semantic_search_publications” functional
- “get_semantic_map” reworded the description of “subset” cosmetic
- “get_similar_items” reworded the description of “subset” cosmetic
- 9 Oct 26 0
- Tool coverage: 85% → 64% ▼ functional
- Schema quality: 250 → 162 ▲ functional
- 28 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Nov 2026 · Probed https://islam.zmo.de/mcp/
TLS valid
Negotiated TLS 1.2 with TLS_ECDHE_ECDSA_WITH_AES_256_GCM_SHA384 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=*.zmo.de | CN=GEANT TLS ECC 1,O=Hellenic Academic and Research Institutions CA,C=GR | 5 Aug 2026 | 20 Feb 2027 | ECDSA 256 | ECDSA-SHA384 | 39b16c47f1aeb1eb74e2afff9e5357c8 |
| SANs: *.zmo.de, zmo.de | ||||||
| CN=GEANT TLS ECC 1,O=Hellenic Academic and Research Institutions CA,C=GR (CA) | CN=HARICA TLS ECC Root CA 2021,O=Hellenic Academic and Research Institutions CA,C=GR | 3 Jan 2025 | 31 Dec 2039 | ECDSA 384 | ECDSA-SHA384 | 42fddce1261607e1a5e6935a400161dd |
| CN=HARICA TLS ECC Root CA 2021,O=Hellenic Academic and Research Institutions CA,C=GR (CA) | CN=HARICA TLS ECC Root CA 2021,O=Hellenic Academic and Research Institutions CA,C=GR | 19 Feb 2021 | 13 Feb 2045 | ECDSA 384 | ECDSA-SHA384 | 67749d8d77d83b6adb22f4ff59e2bfce |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of islam.zmo.de. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| de. | present | 26755 | 8 | Verified |
| zmo.de. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
| Header | Value |
|---|---|
| strict-transport-security | max-age=63072000; includeSubDomains; preload |
| content-security-policy | frame-ancestors 'self' https://fmadore.github.io https://www.frederickmadore.com https://frederickmadore.com https://slides.frederickmadore.com |
| x-content-type-options | nosniff |
| referrer-policy | strict-origin-when-cross-origin |
| permissions-policy | geolocation=(), midi=(), camera=() |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://islam.zmo.de/mcp/ | Verified | 200 | |
| http (plaintext) | http://islam.zmo.de/mcp/ | HTTPS enforced |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
explore_corpus Research workbench ~158
Selection workbench: items, concordance, coverage, compare (requires comparison), attention, aliases, or paginated manifest/CSL-JSON/BibTeX exports. Exact filters intersect. limit/offset also page compare/coverage/attention cells. Coverage measures archive availability. Exports identify this page and dataset snapshot; compare snapshot IDs across pages. Schema discovery: iwac://datasets/{subset}.
| Name | Type | Req | Description |
|---|---|---|---|
| comparison | object | – | – |
| limit | integer | – | – |
| link | boolean | – | Export modes: link the whole selection (≤5000) as one file instead of a page |
| mode | string | – | – |
| offset | integer | – | – |
| selection | object | – | – |
| subset | string | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| export | object | – | – |
| filters | object | yes | – |
| has_more | boolean | – | – |
| limit | number | – | – |
| metrics | object | – | – |
| mode | string | – | – |
| note | string | – | – |
| offset | number | – | – |
| omitted_cells | number | – | – |
| overlap | number | – | – |
| rows | array | yes | – |
| selections | array | – | – |
| source_exact_field | string | – | – |
| source_field | string | – | – |
| subset | string | yes | – |
| temporal | object | – | – |
| total_cells | number | – | – |
| total_matches | number | yes | – |
| view | string | yes | – |
No examples provided.
fetch Fetch IWAC item ~148
Retrieve the full text and metadata of one IWAC item by an id returned from `search` (format '<category>:<number>', e.g. 'articles:28576'). Returns {id, title, text, url, metadata}: `text` is the item's OCR / abstract / transcription / description, `url` is the canonical islam.zmo.de link to cite, and `metadata` holds the remaining fields (author, date, country, newspaper, AI sentiment, …). Categories: articles, publications, references, documents, index, audiovisual, images.
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | Item id from search, e.g. 'articles:28576' or 'references:11045' |
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | yes | – |
| id | string | yes | – |
| metadata | object | yes | – |
| recommended_tool | string | – | – |
| recommended_usage | object | – | – |
| text | string | yes | – |
| text_source | string | – | – |
| text_truncated | boolean | – | – |
| title | string | – | – |
| url | string | – | – |
No examples provided.
get_article Get article details ~141
Get one article (by id): full metadata, the AI abstract (description_ai), AI sentiment, and OCR text, in 25k-char parts (follow `next_offset`). Pass a `keyword` to get ~2000-char excerpts around each match instead.
| Name | Type | Req | Description |
|---|---|---|---|
| article_id | integer | yes | – |
| context_chars | integer | – | Default 2000, max 5000 |
| keyword | string | – | Return excerpts around matches instead of the full OCR (accent-insensitive) |
| max_excerpts | integer | – | Default 10, max 25 |
| offset | integer | – | Read from this character on: the previous part's next_offset |
No output schema declared.
No examples provided.
get_audiovisual Get audiovisual details ~153
Get one audiovisual record by id: full description and transcription (where one exists), creator/publishing channel, duration, medium, subjects, places, language, rights, source, and three distinct links: `url` (the IWAC page, the one to cite), `external_url` (where a harvested video plays) and `media_url` (a deposited file). `source_type` says which to expect. A long transcription comes in 25k-char parts (follow `next_offset`); `keyword` returns excerpts instead.
| Name | Type | Req | Description |
|---|---|---|---|
| audiovisual_id | integer | yes | – |
| keyword | string | – | – |
| offset | integer | – | Read from this character on: the previous part's next_offset |
No output schema declared.
No examples provided.
get_collection_stats Collection statistics ~53
Overall statistics for every IWAC subset, including `fulltext_coverage` — how many items in each subset actually carry searchable full text in this dataset. Read that before treating any keyword count as a full-text census.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| articles_by_country | object | – | – |
| collection_name | string | yes | – |
| dataset_url | string | yes | – |
| date_range | object | – | – |
| failed_subsets | array | – | – |
| fulltext_coverage | object | – | – |
| fulltext_note | string | – | – |
| newspaper_count | number | – | – |
| subset_counts | object | yes | – |
| total_records | number | yes | – |
| view | string | yes | – |
No examples provided.
get_cooccurrence Co-occurrence matrix ~248
Count pairs of metadata values co-tagged on the same items. Matrix/network views show descriptive associations, not causal links. Filters apply before pair counting; top_n caps the vocabulary.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| field | string | – | subject (default) | spatial | author | language |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| newspaper | string | – | Newspaper/periodical substring |
| subject | string | – | Exact tag |
| subset | string | – | articles (default) | publications | references |
| top_n | integer | – | Values on each axis (default 15, max 30) |
| Name | Type | Req | Description |
|---|---|---|---|
| field | string | yes | – |
| filters | object | yes | – |
| matrix | array | yes | – |
| note | string | – | – |
| subset | string | yes | – |
| top_pairs | array | yes | – |
| total_matches | number | yes | – |
| values | array | yes | – |
| view | string | yes | – |
No examples provided.
get_country_comparison Compare countries ~33
Compare article counts, newspaper counts, date ranges, and claude-haiku-5-5 polarity across countries.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| countries | array | yes | – |
| polarity_model | string | – | – |
| total_countries | number | yes | – |
| view | string | yes | – |
No examples provided.
get_document Get document details ~140
Get one archival document (by id): full metadata, AI description, and OCR text, in 25k-char parts (follow `next_offset`). Pass a `keyword` to get ~2000-char excerpts around each match instead, useful for long documents.
| Name | Type | Req | Description |
|---|---|---|---|
| context_chars | integer | – | Default 2000, max 5000 |
| document_id | integer | yes | – |
| keyword | string | – | Return excerpts around matches instead of the full OCR (accent-insensitive) |
| max_excerpts | integer | – | Default 10, max 25 |
| offset | integer | – | Read from this character on: the previous part's next_offset |
No output schema declared.
No examples provided.
get_field_distribution Rank a field's values ~267
Rank exact metadata values, splitting pipe-separated tags. Reports missing metadata and optional coverage over time. Choose spatial for mentioned places, country for stored country tags, or subject/author/language.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| field | string | yes | subject | spatial | author | language | newspaper | country |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| newspaper | string | – | Newspaper/periodical substring |
| over_time | boolean | – | Also return the per-year share of items carrying a value |
| subject | string | – | Exact tag |
| subset | string | – | articles (default) | publications | references |
| top_n | integer | – | Values returned (default 25, max 100) |
| Name | Type | Req | Description |
|---|---|---|---|
| coverage_by_year | object | – | – |
| distinct_values | number | yes | – |
| field | string | yes | – |
| filters | object | yes | – |
| items_with_value | number | yes | – |
| note | string | – | – |
| other_values | number | – | – |
| subset | string | yes | – |
| total_matches | number | yes | – |
| values | array | yes | – |
| view | string | yes | – |
No examples provided.
get_image Get photograph details ~59
Get one photograph by id: title, photographer, capture date, place and coordinates, subjects, rights, the IIIF manifest, and the full-resolution `image_url`. The server returns URLs, not image bytes.
| Name | Type | Req | Description |
|---|---|---|---|
| image_id | integer | yes | – |
No output schema declared.
No examples provided.
get_index_entry Get index entry details ~44
Get full details of an index entry by id (raw dataset columns, French names — Titre, Prénom, Coordonnées…).
| Name | Type | Req | Description |
|---|---|---|---|
| entry_id | integer | yes | – |
No output schema declared.
No examples provided.
get_lexical_metrics Press language metrics ~237
Text length, lexical richness and readability by country/newspaper/year. Metrics are precomputed; readability is French-specific and excludes other languages. Missing values are disclosed. Compare distributions as descriptive evidence.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| group_by | string | – | year (default) | newspaper | country |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| newspaper | string | – | Newspaper/periodical substring |
| subject | string | – | Exact tag |
| top_n | integer | – | Groups returned when grouping by newspaper (default 20, max 60) |
| Name | Type | Req | Description |
|---|---|---|---|
| filters | object | yes | – |
| group_by | string | yes | – |
| groups | array | yes | – |
| metrics | object | yes | – |
| note | string | – | – |
| readability_excluded | number | – | – |
| total_matches | number | yes | – |
| view | string | yes | – |
No examples provided.
get_newspaper_stats Newspaper statistics ~49
Per-newspaper article counts and date ranges.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| Name | Type | Req | Description |
|---|---|---|---|
| country_filter | string | – | – |
| newspapers | array | yes | – |
| total_articles | number | yes | – |
| total_newspapers | number | yes | – |
| view | string | yes | – |
No examples provided.
get_place_distribution Places on a map ~218
Place tags joined to authority coordinates. Separates publication countries from mentioned places; missing geocodes are counted explicitly.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| newspaper | string | – | Newspaper/periodical substring |
| subject | string | – | Exact tag |
| subset | string | – | articles (default) | publications | references |
| top_n | integer | – | Geocoded places returned (default 60, max 200) |
| Name | Type | Req | Description |
|---|---|---|---|
| filters | object | yes | – |
| geocode_coverage | object | – | – |
| items_by_country | object | – | – |
| items_with_place | number | yes | – |
| note | string | – | – |
| places | array | yes | – |
| subset | string | yes | – |
| total_matches | number | yes | – |
| ungeocoded | array | – | – |
| ungeocoded_mentions | number | – | – |
| view | string | yes | – |
No examples provided.
get_publication_fulltext Get publication full text ~121
Full OCR text of a publication in 25k-char parts (follow `next_offset`), or ~2000-char excerpts around keyword matches (accent-insensitive; capped: see match_count vs excerpts_returned).
| Name | Type | Req | Description |
|---|---|---|---|
| context_chars | integer | – | Default 2000, max 5000 |
| keyword | string | – | – |
| max_excerpts | integer | – | Default 10, max 25 |
| offset | integer | – | Read from this character on: the previous part's next_offset |
| publication_id | integer | yes | – |
No output schema declared.
No examples provided.
get_reference Get reference details ~60
Full bibliographic record for one academic reference (by id), including the complete abstract (present for ~51% of references), subjects, DOI/URL, and host-work details (book, volume, issue, pages).
| Name | Type | Req | Description |
|---|---|---|---|
| reference_id | integer | yes | – |
No output schema declared.
No examples provided.
get_semantic_map Semantic scatter ~278
Stable-hash sample of matching stored embeddings, projected with PCA. Reports eligible, invalid, missing and capped counts, seed and explained variance. Group counts describe the sample. Coordinates are chart-only; this is not the published UMAP landscape. Needs no API key.
| Name | Type | Req | Description |
|---|---|---|---|
| color_by | string | – | country | newspaper | subject | lda_topic_label | polarity (claude-haiku-5-5's label) |
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| limit | integer | – | Items projected (default 300, max 2000) |
| newspaper | string | – | Newspaper/periodical substring |
| subject | string | – | Exact tag |
| subset | string | – | articles (default) | documents | publications | references |
| Name | Type | Req | Description |
|---|---|---|---|
| color_by | string | – | – |
| eligible_embeddings | number | – | – |
| explained_variance | array | yes | – |
| filters | object | yes | – |
| groups | object | – | – |
| invalid_embeddings | number | – | – |
| limit_warning | string | – | – |
| missing_embeddings | number | – | – |
| note | string | yes | – |
| omitted_by_limit | number | – | – |
| points | array | – | – |
| projected | number | yes | – |
| requested_limit | number | – | – |
| sampling | string | – | – |
| seed | string | – | – |
| subset | string | yes | – |
| total_matches | number | yes | – |
| view | string | yes | – |
No examples provided.
get_sentiment_distribution Aggregate AI sentiment ~344
Aggregate AI labels over a shared selection. model:"all" compares independent annotators and their coverage; model:"consensus" reads the stored panel majority. Choose compare_models and agreement_field for pairwise Cohen's kappa and quadratic weighted kappa, with explicit denominators. Labels are interpretations, not ground truth; subjectivity is weak evidence and its caveat must accompany findings.
| Name | Type | Req | Description |
|---|---|---|---|
| agreement_field | string | – | – |
| compare_models | array | – | Pair of model IDs or aliases; requires model:"all" |
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| model | string | – | gpt-5-6-luna | mistral-small-2603 | deepseek-v4-flash-0731 | gemma-4-31b-it | qwen3-8-27b | claude-haiku-5-5 | all | consensus; default claude-haiku-5-5. Vendor aliases accepted; retired models rejec… |
| newspaper | string | – | Newspaper/periodical substring |
| subject | string | – | Exact tag |
| Name | Type | Req | Description |
|---|---|---|---|
| agreement | object | – | – |
| agreement_matrix | object | – | – |
| by_model | object | – | – |
| centrality_distribution | object | – | – |
| consensus | object | – | – |
| coverage | object | – | – |
| disputed | object | – | – |
| filters | object | yes | – |
| instrument_ids | object | – | – |
| model | string | yes | – |
| model_caveat | string | – | – |
| models | array | – | – |
| note | string | – | – |
| polarity_distribution | object | – | – |
| subjectivity | object | – | – |
| subjectivity_median_rank | object | – | – |
| total_articles | number | yes | – |
| view | string | yes | – |
No examples provided.
get_similar_items Find similar items ~161
Nearest stored embeddings by cosine similarity. Articles and documents lead with the dataset's published top 10. Scores run high (unrelated ~0.7) and rank reading candidates; >= 0.97 suggests a near-duplicate, but no threshold proves a reprint. Returns source IDs and dates. Corpus-wide candidate generation belongs offline.
| Name | Type | Req | Description |
|---|---|---|---|
| id | string | yes | Item id — either a bare o:id ('3064') or the namespaced form search returns ('articles:3064') |
| limit | integer | – | Neighbours returned (default 12, max 50) |
| min_score | number | – | Minimum cosine similarity (-1 to 1) |
| subset | string | – | articles (default) | documents | publications | references |
| Name | Type | Req | Description |
|---|---|---|---|
| neighbours | array | yes | – |
| neighbours_source | string | yes | – |
| note | string | yes | – |
| source | object | yes | – |
| stored_count | number | yes | – |
| subset | string | yes | – |
| view | string | yes | – |
No examples provided.
get_temporal_distribution Coverage over time ~354
Counts by Gregorian or Hijri year/month, or pooled lunar month. Group by country/newspaper. Partial dates and missing lunar dates are disclosed. normalize_by returns numerator counts and per-bucket denominators in the same country/outlet/date scope, removing thematic filters. Shares describe IWAC holdings.
| Name | Type | Req | Description |
|---|---|---|---|
| calendar | string | – | gregorian (default) | hijri — bucket by the Islamic (Umm al-Qura) calendar |
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| granularity | string | – | year (default) | month | lunar_month (all years collapsed into 12 lunar months; needs calendar=hijri) |
| group_by | string | – | country | newspaper — one distribution per group value |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| newspaper | string | – | Newspaper/periodical substring |
| normalize_by | string | – | Share per bucket in the same country/outlet/date scope; searchable restricts both counts to full text. Thematic filters are removed from the denominator. |
| subject | string | – | Exact tag |
| subset | string | – | articles (default) | publications | references | documents | audiovisual | images |
| Name | Type | Req | Description |
|---|---|---|---|
| calendar | string | – | – |
| dated_count | number | yes | – |
| denominator_filters | object | – | – |
| denominators | object | – | – |
| distribution | object | – | – |
| distribution_by_group | object | – | – |
| filters | object | yes | – |
| granularity | string | yes | – |
| group_by | string | – | – |
| imprecise_date_count | number | – | – |
| invalid_date_count | number | – | – |
| month_labels | object | – | – |
| normalize_by | string | – | – |
| note | string | – | – |
| subset | string | yes | – |
| total_matches | number | yes | – |
| undated_count | number | yes | – |
| view | string | yes | – |
No examples provided.
get_topic_distribution Topic distribution ~270
Counts of offline LDA topic assignments, optionally over time. Topic labels are interpretive model outputs; exact topic_id filters select assignments rather than keyword matches. Reports unclassified coverage.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name (accents optional) |
| date_from | string | – | Inclusive date bounds: YYYY[-MM[-DD]] |
| date_to | string | – | – |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| hijri_month | string | – | – |
| hijri_year | integer | – | – |
| keyword | string | – | – |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| min_prob | number | – | 0-1; keep only assignments at or above this probability |
| newspaper | string | – | Newspaper/periodical substring |
| over_time | boolean | – | Also return per-year counts for the leading topics |
| subject | string | – | Exact tag |
| subset | string | – | articles (default) | references |
| top_n | integer | – | Topics given their own band in over_time (default 8, max 15) |
| Name | Type | Req | Description |
|---|---|---|---|
| classified | number | yes | – |
| filters | object | yes | – |
| note | string | – | – |
| periods | array | – | – |
| series_by_topic | object | – | – |
| span | array | – | – |
| subset | string | yes | – |
| topics | array | yes | – |
| total_matches | number | yes | – |
| trend_by_topic | object | – | – |
| view | string | yes | – |
No examples provided.
list_audiovisual List audiovisual materials ~183
List audiovisual materials, newest first (francophone web video from Burkina Faso, Togo and Benin; deposited Nigerian Hausa/Arabic recordings). Filter by country, publishing channel or `source_type`.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Burkina Faso, Togo, Benin and Nigeria only — no Niger or Ivorian items |
| limit | integer | – | Default 20, max 50 |
| offset | integer | – | – |
| publisher | string | – | Substring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI |
| source_type | string | – | youtube (harvested web video, the large majority) | deposited (recordings with a file, 47) |
No output schema declared.
No examples provided.
list_locations List lieux from the index ~161
List lieux from the IWAC index, sorted by frequency (most-referenced first). The optional 'country' filter selects entries that APPEAR IN records from that country (mentioned-in, not located-in), ranked by collection-wide 'frequency' — so foreign and cross-border entries can appear. Nigeria reaches only the few entries its references mention (index frequency counts articles, publications and references; no article is Nigerian).
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Selects lieux MENTIONED IN records from that country, not entities located there |
| limit | integer | – | Default 50, max 200 |
| offset | integer | – | – |
No output schema declared.
No examples provided.
list_periodicals List periodicals ~76
List the Islamic periodical/series titles in the publications subset, with issue counts and year ranges. Use the returned newspaper value as the `newspaper` filter on search_publications.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| Name | Type | Req | Description |
|---|---|---|---|
| country_filter | string | – | – |
| periodicals | array | yes | – |
| total_periodicals | number | yes | – |
| view | string | yes | – |
No examples provided.
list_persons List personnes from the index ~162
List personnes from the IWAC index, sorted by frequency (most-referenced first). The optional 'country' filter selects entries that APPEAR IN records from that country (mentioned-in, not located-in), ranked by collection-wide 'frequency' — so foreign and cross-border entries can appear. Nigeria reaches only the few entries its references mention (index frequency counts articles, publications and references; no article is Nigerian).
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Selects personnes MENTIONED IN records from that country, not entities located there |
| limit | integer | – | Default 50, max 200 |
| offset | integer | – | – |
No output schema declared.
No examples provided.
list_subjects List sujets from the index ~47
List sujets from the IWAC index, sorted by frequency (most-referenced first).
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Default 50, max 200 |
| offset | integer | – | – |
No output schema declared.
No examples provided.
search Search IWAC ~308
Search the Islam West Africa Collection across newspaper articles, Islamic publications, archival documents, academic references, audiovisual recordings, photographs, and the authority index (persons/places/organisations/events/subjects). Pass ONE concept or name — e.g. 'Tijaniyya', 'laïcité', 'Sheikh Gumi', 'pèlerinage'. Matching is accent- and case-insensitive; a multi-word query requires every word to appear somewhere in the item, so prefer a single concept per call. Write query strings and concept keywords in French for press/publication/document/index discovery even when the user's report language is not French. Academic references are multilingual, so try French and English title/abstract terms when relevant; metadata/filter labels remain French. Use the French transliteration of Islamic terms (Tabaski not 'Eid al-Adha', charia not 'sharia', Maouloud not 'Mawlid'). Returns {results:[{id,title,url,category}], ranking}; each result's `category` names its subset and the `ranking` field documents the ordering. Pass an id to `fetch` to read the full text. For filtered queries (by country, date, or newspaper) use the search_* tools instead.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Max results across all categories. Default 20, max 50. |
| query | string | yes | One concept, name, or short phrase; use French concept terms for primary sources, and French/English terms for references |
| Name | Type | Req | Description |
|---|---|---|---|
| count | integer | yes | – |
| coverage_warning | string | – | – |
| deep_scan | boolean | yes | – |
| limit | integer | yes | – |
| limit_warning | string | – | – |
| ranking | string | yes | – |
| requested_limit | integer | – | – |
| results | array | yes | – |
| search_coverage | object | – | – |
| unavailable_categories | array | – | – |
No examples provided.
search_articles Search newspaper articles ~411
Search IWAC newspaper articles by keyword (title + OCR + AI abstracts, French and English), country, newspaper, subject, and date range. Use French concept keywords regardless of the user's report language. Matching is accent- and case-insensitive.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| date_from | string | – | YYYY-MM-DD (or YYYY) |
| date_to | string | – | YYYY-MM-DD (or YYYY) |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| hijri_month | string | – | Islamic lunar month: 1-12, or a name (Ramadan, Chaabane, Chawwal, Dhu al-Hijja). Pulls the articles behind an observance peak — matches only items with a full YYYY-MM-DD date. |
| hijri_year | integer | – | Islamic (Umm al-Qura) year, e.g. 1445 |
| keyword | string | – | Concept keyword; every word must occur (any order) in the title, OCR or French/English AI abstracts; "quote" a phrase. Prefer French for the OCR; an English term still matches via the English abstract |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| limit | integer | – | Default 20, max 100 (10 and 25 with with_description) |
| newspaper | string | – | – |
| offset | integer | – | – |
| subject | string | – | – |
| with_description | boolean | – | Include each article's ~500-char AI abstract (description_ai) for triage without get_article. Adds ~125 tokens/row, so `limit` defaults to 10 and caps at 25 while this is on. |
No output schema declared.
No examples provided.
search_audiovisual Search audiovisual materials ~354
Search audiovisual materials by keyword and metadata: francophone web video from Burkina Faso, Togo and Benin (TV reports, association and campus recordings), plus deposited Nigerian Hausa/Arabic recordings. Keyword matches title, creator, publisher, subject, spatial, language, source, the item's own description (the richest text most of these items have) and its transcription where one exists. Each row says which population it is from (`source_type`) and carries either `external_url` (a video to watch) or `media_url` (a file), never both.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Burkina Faso, Togo, Benin and Nigeria only — no Niger or Ivorian items |
| keyword | string | – | Every word must occur across the title/metadata fields; "quote" a phrase |
| language | string | – | Exact language value, e.g. Français | Haoussa | Arabe | Anglais | Mooré |
| limit | integer | – | Default 20, max 50 |
| medium | string | – | Exact carrier medium: Vidéo sur le web | DVD | CD (validated, accents optional) |
| offset | integer | – | – |
| publisher | string | – | Substring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI |
| source_type | string | – | youtube (harvested web video, the large majority) | deposited (recordings with a file, 47) |
| subject | string | – | Exact subject tag — only ~27 rows carry one, so prefer publisher/keyword |
No output schema declared.
No examples provided.
search_by_sentiment Filter articles by AI sentiment ~301
Filter articles by claude-haiku-5-5 sentiment labels (accent/case-insensitive exact match). One model's reading, not a consensus — 5 other models scored the same articles and often disagree; get_sentiment_distribution with model:"all" shows by how much. `subjectivity` is much the weakest of the three scales, so treat a set selected on it as a lead to read rather than as a finding.
| Name | Type | Req | Description |
|---|---|---|---|
| centrality | string | – | Très central | Central | Secondaire | Marginal | Non abordé |
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| disputed | string | – | polarite | centralite | subjectivite — keep only articles the panel SPLIT on for that field (French field names, as stored). Selects contested readings, not a sentiment value. |
| limit | integer | – | Default 20, max 100 |
| offset | integer | – | – |
| polarity | string | – | Très positif | Positif | Neutre | Négatif | Très négatif | Non applicable |
| subject | string | – | – |
| subjectivity | string | – | Très objectif | Plutôt objectif | Mixte | Plutôt subjectif | Très subjectif — least to most subjective. Unscored where the model answered Non abordé, so this filter also excludes those. |
No output schema declared.
No examples provided.
search_documents Search archival documents ~157
Search the small archival-documents subset (~26 items: Islamic association reports, flyers, project documents — mostly Burkina Faso). Use French concept keywords regardless of the user's report language. Most have OCR text and an AI description. Call with no arguments to list all.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Corpus is mostly Burkina Faso/Togo/Benin |
| keyword | string | – | Concept keyword; every word must occur in the title, OCR, French/English AI descriptions or subject; "quote" a phrase |
| limit | integer | – | Default 15, max 50 |
| offset | integer | – | – |
No output schema declared.
No examples provided.
search_images Search photographs ~270
Search the IWAC photographs (30 items: mosques, radio stations, schools, signage and street scenes documented during fieldwork). Keyword matches title, creator, subject, place and the rare caption. Each result carries `image_url` (the full-resolution file), `coordinates` ('lat, lng' where known) and the canonical IWAC page. Call with no arguments to list all. Captions are almost never present, so prefer subject/place filters over keywords, or semantic_search_images when it is enabled.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional) |
| creator | string | – | Photographer name (substring match) |
| date_from | string | – | YYYY-MM-DD (or YYYY) |
| date_to | string | – | YYYY-MM-DD (or YYYY) |
| keyword | string | – | French concept keyword; every word must occur in the title, creator, subject, place or caption; "quote" a phrase |
| limit | integer | – | Default 20, max 50 |
| offset | integer | – | – |
| spatial | string | – | Exact place name, e.g. Ouagadougou (pipe-aware) |
| subject | string | – | Exact subject tag (pipe-aware) |
No output schema declared.
No examples provided.
search_index Search authority index ~137
Search the IWAC authority index (persons, places, organisations, events, subjects) by name. Accent/case-insensitive.
| Name | Type | Req | Description |
|---|---|---|---|
| index_type | string | – | Exact type (accents optional), validated against: Personnes | Lieux | Organisations | Événements | Sujets | Notices d'autorité. An unrecognised value returns an error listing the valid types. |
| keyword | string | yes | Every word must occur in the entry title (any order); "quote" a phrase, or give a whole alternate title |
| limit | integer | – | Default 20, max 100 |
| offset | integer | – | – |
No output schema declared.
No examples provided.
search_publications Search publications ~380
Search Islamic publications (periodical issues, books). `keyword` matches title, subject, table of contents, and full OCR text (TOC hits come back as matching_toc_entries); use French concept keywords regardless of the user's report language. Filter by newspaper/series, subject, country and year. Use list_periodicals to discover series titles, and get_publication_fulltext for keyword excerpts from a single issue.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| date_from | string | – | Earliest year, YYYY |
| date_to | string | – | Latest year, YYYY |
| exact | object | – | AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>. |
| hijri_month | string | – | Islamic lunar month: 1-12, or a name (Ramadan, Chaabane, Chawwal, Dhu al-Hijja). Matches only issues with a full YYYY-MM-DD date — ~83% of them. |
| hijri_year | integer | – | Islamic (Umm al-Qura) year, e.g. 1445 |
| keyword | string | – | French concept keyword; every word must occur in the title, subject, table of contents or OCR; "quote" a phrase |
| keyword_aliases | array | – | – |
| keyword_mode | string | – | literal: the whole keyword as one substring |
| limit | integer | – | Default 20, max 100 |
| newspaper | string | – | Periodical/series title (see list_periodicals) |
| offset | integer | – | – |
| subject | string | – | Subject tag (~87% of issues are tagged) |
No output schema declared.
No examples provided.
search_references Search academic references ~339
Search academic references (journal articles, book chapters, theses, books, reports) by keyword and metadata. `keyword` requires every word in the title + abstract ("quote" a phrase). References are multilingual: try French and English title/abstract keywords when relevant; metadata/filter values such as `reference_type` and `language` use French labels. Results include a short abstract snippet — use get_reference for the full abstract and bibliographic detail.
| Name | Type | Req | Description |
|---|---|---|---|
| author | string | – | – |
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional) |
| date_from | string | – | Earliest year, YYYY |
| date_to | string | – | Latest year, YYYY |
| keyword | string | – | French or English concept keyword; every word must occur in the title + abstract; "quote" a phrase |
| language | string | – | e.g. Français | Anglais |
| limit | integer | – | Default 20, max 100 |
| offset | integer | – | – |
| reference_type | string | – | Substring match. Values: Article de revue | Chapitre de livre | Livre | Mémoire de maitrise | Rapport | Thèse de doctorat | Communication scientifique | Compte rendu de livre | Article d'encyclopédie… |
| subject | string | – | Subject tag (sparse: ~27% of references are tagged) |
No output schema declared.
No examples provided.
semantic_search_articles Semantic search for articles ~156
Semantic search over article title + full text, including articles whose OCR is not public. Query in any language. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| date_from | string | – | YYYY-MM-DD (or YYYY) |
| date_to | string | – | YYYY-MM-DD (or YYYY) |
| limit | integer | – | Default 10, max 50 |
| newspaper | string | – | – |
| query | string | yes | Natural-language query, any language |
No output schema declared.
No examples provided.
semantic_search_images Semantic search for photographs ~165
Find photographs by describing what they SHOW, in any language ('mosquée en construction', 'street signage in Arabic'). This is cross-modal: the ranking runs against a multimodal embedding of the photograph itself, not against a caption, so it works even though only 2 of the 30 images have one. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional) |
| limit | integer | – | Default 10, max 30 |
| query | string | yes | Description of the visual content, any language |
No output schema declared.
No examples provided.
semantic_search_publications Semantic search for publications ~158
Semantic search over publication tables of contents, present for ~40% of issues (none for An-Nasr Vendredi, 130 of 695 Islam Info issues): use search_publications for the rest. Rows show the first 600 characters of each table. Query in any language. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional) |
| limit | integer | – | Default 10, max 50 |
| query | string | yes | Natural-language query, any language |
No output schema declared.
No examples provided.
semantic_search_references Semantic search for academic references ~196
Semantic search over academic references by title + abstract, across languages. Only references with an abstract (about half) are covered; use search_references for the rest. Runs the corpus model, EmbeddingGemma 2, locally with no API key (first use downloads ~350 MB). similarity_score only ranks within one query.
| Name | Type | Req | Description |
|---|---|---|---|
| country | string | – | Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional) |
| date_from | string | – | Earliest year, YYYY |
| date_to | string | – | Latest year, YYYY |
| language | string | – | e.g. Français | Anglais |
| limit | integer | – | Default 10, max 50 |
| query | string | yes | Natural-language query, any language |
| reference_type | string | – | French type label, substring (e.g. Thèse de doctorat) |
No output schema declared.
No examples provided.
How do I install the Islam West Africa Collection (IWAC) MCP server?
Islam West Africa Collection (IWAC) is a hosted endpoint at https://islam.zmo.de/mcp/, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · islam.zmo.de
claude mcp add --transport http fmadore-iwac-mcp-server 'https://islam.zmo.de/mcp/'
What is the Islam West Africa Collection (IWAC) MCP server?
Islam West Africa Collection (IWAC) is an MCP server listed in the public MCP registry as io.github.fmadore/iwac-mcp-server. Read-only access to the Islam West Africa Collection via Hugging Face datasets. This page covers its hosted endpoint (https://islam.zmo.de/mcp/).
Is the Islam West Africa Collection (IWAC) MCP server safe to use?
Islam West Africa Collection (IWAC) scores 87 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Islam West Africa Collection (IWAC) MCP server expose?
Islam West Africa Collection (IWAC) exposes 39 tools: search, fetch, explore_corpus, search_articles, get_article, and 34 more. Their descriptions and schemas cost roughly 7,497 tokens of context every time the server is loaded.
Does the Islam West Africa Collection (IWAC) MCP server require authentication?
No. We connected to Islam West Africa Collection (IWAC) without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the Islam West Africa Collection (IWAC) MCP server still maintained?
Islam West Africa Collection (IWAC) is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.