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Islam West Africa Collection (IWAC)

REMOTE · ISLAM.ZMO.DE · 3 COMPONENTS

Read-only access to the Islam West Africa Collection via Hugging Face datasets.

0 this week 87 Trust /100

Last scanned (17 hours ago)

Scores higher than 94% of remote servers

Reachable. Last reached 4 Nov 2026.

Category Education and Research

Trust breakdown (7 categories)

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
Transport & Reachability100
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
Changelog

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
Diagnostics

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
MCP tools · 39 exposed · ~7,497 tokens

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 →

Tool Tokens
explore_corpus ~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}.

NameTypeReqDescription
comparisonobject––
limitinteger––
linkboolean–Export modes: link the whole selection (≤5000) as one file instead of a page
modestring––
offsetinteger––
selectionobject––
subsetstring––
NameTypeReqDescription
exportobject––
filtersobjectyes–
has_moreboolean––
limitnumber––
metricsobject––
modestring––
notestring––
offsetnumber––
omitted_cellsnumber––
overlapnumber––
rowsarrayyes–
selectionsarray––
source_exact_fieldstring––
source_fieldstring––
subsetstringyes–
temporalobject––
total_cellsnumber––
total_matchesnumberyes–
viewstringyes–

No examples provided.

fetch ~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.

NameTypeReqDescription
idstringyesItem id from search, e.g. 'articles:28576' or 'references:11045'
NameTypeReqDescription
categorystringyes–
idstringyes–
metadataobjectyes–
recommended_toolstring––
recommended_usageobject––
textstringyes–
text_sourcestring––
text_truncatedboolean––
titlestring––
urlstring––

No examples provided.

get_article ~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.

NameTypeReqDescription
article_idintegeryes–
context_charsinteger–Default 2000, max 5000
keywordstring–Return excerpts around matches instead of the full OCR (accent-insensitive)
max_excerptsinteger–Default 10, max 25
offsetinteger–Read from this character on: the previous part's next_offset

No output schema declared.

No examples provided.

get_audiovisual ~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.

NameTypeReqDescription
audiovisual_idintegeryes–
keywordstring––
offsetinteger–Read from this character on: the previous part's next_offset

No output schema declared.

No examples provided.

get_collection_stats ~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.

NameTypeReqDescription
articles_by_countryobject––
collection_namestringyes–
dataset_urlstringyes–
date_rangeobject––
failed_subsetsarray––
fulltext_coverageobject––
fulltext_notestring––
newspaper_countnumber––
subset_countsobjectyes–
total_recordsnumberyes–
viewstringyes–

No examples provided.

get_cooccurrence ~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.

NameTypeReqDescription
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
fieldstring–subject (default) | spatial | author | language
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
newspaperstring–Newspaper/periodical substring
subjectstring–Exact tag
subsetstring–articles (default) | publications | references
top_ninteger–Values on each axis (default 15, max 30)
NameTypeReqDescription
fieldstringyes–
filtersobjectyes–
matrixarrayyes–
notestring––
subsetstringyes–
top_pairsarrayyes–
total_matchesnumberyes–
valuesarrayyes–
viewstringyes–

No examples provided.

get_country_comparison ~33

Compare article counts, newspaper counts, date ranges, and claude-haiku-5-5 polarity across countries.

Input schema present but exposes no named parameters.

NameTypeReqDescription
countriesarrayyes–
polarity_modelstring––
total_countriesnumberyes–
viewstringyes–

No examples provided.

get_document ~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.

NameTypeReqDescription
context_charsinteger–Default 2000, max 5000
document_idintegeryes–
keywordstring–Return excerpts around matches instead of the full OCR (accent-insensitive)
max_excerptsinteger–Default 10, max 25
offsetinteger–Read from this character on: the previous part's next_offset

No output schema declared.

No examples provided.

get_field_distribution ~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.

NameTypeReqDescription
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
fieldstringyessubject | spatial | author | language | newspaper | country
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
newspaperstring–Newspaper/periodical substring
over_timeboolean–Also return the per-year share of items carrying a value
subjectstring–Exact tag
subsetstring–articles (default) | publications | references
top_ninteger–Values returned (default 25, max 100)
NameTypeReqDescription
coverage_by_yearobject––
distinct_valuesnumberyes–
fieldstringyes–
filtersobjectyes–
items_with_valuenumberyes–
notestring––
other_valuesnumber––
subsetstringyes–
total_matchesnumberyes–
valuesarrayyes–
viewstringyes–

No examples provided.

get_image ~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.

NameTypeReqDescription
image_idintegeryes–

No output schema declared.

No examples provided.

get_index_entry ~44

Get full details of an index entry by id (raw dataset columns, French names — Titre, Prénom, Coordonnées…).

NameTypeReqDescription
entry_idintegeryes–

No output schema declared.

No examples provided.

get_lexical_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.

NameTypeReqDescription
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
group_bystring–year (default) | newspaper | country
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
newspaperstring–Newspaper/periodical substring
subjectstring–Exact tag
top_ninteger–Groups returned when grouping by newspaper (default 20, max 60)
NameTypeReqDescription
filtersobjectyes–
group_bystringyes–
groupsarrayyes–
metricsobjectyes–
notestring––
readability_excludednumber––
total_matchesnumberyes–
viewstringyes–

No examples provided.

get_newspaper_stats ~49

Per-newspaper article counts and date ranges.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
NameTypeReqDescription
country_filterstring––
newspapersarrayyes–
total_articlesnumberyes–
total_newspapersnumberyes–
viewstringyes–

No examples provided.

get_place_distribution ~218

Place tags joined to authority coordinates. Separates publication countries from mentioned places; missing geocodes are counted explicitly.

NameTypeReqDescription
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
newspaperstring–Newspaper/periodical substring
subjectstring–Exact tag
subsetstring–articles (default) | publications | references
top_ninteger–Geocoded places returned (default 60, max 200)
NameTypeReqDescription
filtersobjectyes–
geocode_coverageobject––
items_by_countryobject––
items_with_placenumberyes–
notestring––
placesarrayyes–
subsetstringyes–
total_matchesnumberyes–
ungeocodedarray––
ungeocoded_mentionsnumber––
viewstringyes–

No examples provided.

get_publication_fulltext ~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).

NameTypeReqDescription
context_charsinteger–Default 2000, max 5000
keywordstring––
max_excerptsinteger–Default 10, max 25
offsetinteger–Read from this character on: the previous part's next_offset
publication_idintegeryes–

No output schema declared.

No examples provided.

get_reference ~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).

NameTypeReqDescription
reference_idintegeryes–

No output schema declared.

No examples provided.

get_semantic_map ~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.

NameTypeReqDescription
color_bystring–country | newspaper | subject | lda_topic_label | polarity (claude-haiku-5-5's label)
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
limitinteger–Items projected (default 300, max 2000)
newspaperstring–Newspaper/periodical substring
subjectstring–Exact tag
subsetstring–articles (default) | documents | publications | references
NameTypeReqDescription
color_bystring––
eligible_embeddingsnumber––
explained_variancearrayyes–
filtersobjectyes–
groupsobject––
invalid_embeddingsnumber––
limit_warningstring––
missing_embeddingsnumber––
notestringyes–
omitted_by_limitnumber––
pointsarray––
projectednumberyes–
requested_limitnumber––
samplingstring––
seedstring––
subsetstringyes–
total_matchesnumberyes–
viewstringyes–

No examples provided.

get_sentiment_distribution ~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.

NameTypeReqDescription
agreement_fieldstring––
compare_modelsarray–Pair of model IDs or aliases; requires model:"all"
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
modelstring–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…
newspaperstring–Newspaper/periodical substring
subjectstring–Exact tag
NameTypeReqDescription
agreementobject––
agreement_matrixobject––
by_modelobject––
centrality_distributionobject––
consensusobject––
coverageobject––
disputedobject––
filtersobjectyes–
instrument_idsobject––
modelstringyes–
model_caveatstring––
modelsarray––
notestring––
polarity_distributionobject––
subjectivityobject––
subjectivity_median_rankobject––
total_articlesnumberyes–
viewstringyes–

No examples provided.

get_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.

NameTypeReqDescription
idstringyesItem id — either a bare o:id ('3064') or the namespaced form search returns ('articles:3064')
limitinteger–Neighbours returned (default 12, max 50)
min_scorenumber–Minimum cosine similarity (-1 to 1)
subsetstring–articles (default) | documents | publications | references
NameTypeReqDescription
neighboursarrayyes–
neighbours_sourcestringyes–
notestringyes–
sourceobjectyes–
stored_countnumberyes–
subsetstringyes–
viewstringyes–

No examples provided.

get_temporal_distribution ~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.

NameTypeReqDescription
calendarstring–gregorian (default) | hijri — bucket by the Islamic (Umm al-Qura) calendar
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
granularitystring–year (default) | month | lunar_month (all years collapsed into 12 lunar months; needs calendar=hijri)
group_bystring–country | newspaper — one distribution per group value
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
newspaperstring–Newspaper/periodical substring
normalize_bystring–Share per bucket in the same country/outlet/date scope; searchable restricts both counts to full text. Thematic filters are removed from the denominator.
subjectstring–Exact tag
subsetstring–articles (default) | publications | references | documents | audiovisual | images
NameTypeReqDescription
calendarstring––
dated_countnumberyes–
denominator_filtersobject––
denominatorsobject––
distributionobject––
distribution_by_groupobject––
filtersobjectyes–
granularitystringyes–
group_bystring––
imprecise_date_countnumber––
invalid_date_countnumber––
month_labelsobject––
normalize_bystring––
notestring––
subsetstringyes–
total_matchesnumberyes–
undated_countnumberyes–
viewstringyes–

No examples provided.

get_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.

NameTypeReqDescription
countrystring–Exact country name (accents optional)
date_fromstring–Inclusive date bounds: YYYY[-MM[-DD]]
date_tostring––
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
hijri_monthstring––
hijri_yearinteger––
keywordstring––
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
min_probnumber–0-1; keep only assignments at or above this probability
newspaperstring–Newspaper/periodical substring
over_timeboolean–Also return per-year counts for the leading topics
subjectstring–Exact tag
subsetstring–articles (default) | references
top_ninteger–Topics given their own band in over_time (default 8, max 15)
NameTypeReqDescription
classifiednumberyes–
filtersobjectyes–
notestring––
periodsarray––
series_by_topicobject––
spanarray––
subsetstringyes–
topicsarrayyes–
total_matchesnumberyes–
trend_by_topicobject––
viewstringyes–

No examples provided.

list_audiovisual ~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`.

NameTypeReqDescription
countrystring–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
limitinteger–Default 20, max 50
offsetinteger––
publisherstring–Substring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI
source_typestring–youtube (harvested web video, the large majority) | deposited (recordings with a file, 47)

No output schema declared.

No examples provided.

list_locations ~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).

NameTypeReqDescription
countrystring–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
limitinteger–Default 50, max 200
offsetinteger––

No output schema declared.

No examples provided.

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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
NameTypeReqDescription
country_filterstring––
periodicalsarrayyes–
total_periodicalsnumberyes–
viewstringyes–

No examples provided.

list_persons ~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).

NameTypeReqDescription
countrystring–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
limitinteger–Default 50, max 200
offsetinteger––

No output schema declared.

No examples provided.

list_subjects ~47

List sujets from the IWAC index, sorted by frequency (most-referenced first).

NameTypeReqDescription
limitinteger–Default 50, max 200
offsetinteger––

No output schema declared.

No examples provided.

search ~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.

NameTypeReqDescription
limitinteger–Max results across all categories. Default 20, max 50.
querystringyesOne concept, name, or short phrase; use French concept terms for primary sources, and French/English terms for references
NameTypeReqDescription
countintegeryes–
coverage_warningstring––
deep_scanbooleanyes–
limitintegeryes–
limit_warningstring––
rankingstringyes–
requested_limitinteger––
resultsarrayyes–
search_coverageobject––
unavailable_categoriesarray––

No examples provided.

search_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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
date_fromstring–YYYY-MM-DD (or YYYY)
date_tostring–YYYY-MM-DD (or YYYY)
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
hijri_monthstring–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_yearinteger–Islamic (Umm al-Qura) year, e.g. 1445
keywordstring–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_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
limitinteger–Default 20, max 100 (10 and 25 with with_description)
newspaperstring––
offsetinteger––
subjectstring––
with_descriptionboolean–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 ~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.

NameTypeReqDescription
countrystring–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
keywordstring–Every word must occur across the title/metadata fields; "quote" a phrase
languagestring–Exact language value, e.g. Français | Haoussa | Arabe | Anglais | Mooré
limitinteger–Default 20, max 50
mediumstring–Exact carrier medium: Vidéo sur le web | DVD | CD (validated, accents optional)
offsetinteger––
publisherstring–Substring on the publishing channel/broadcaster, e.g. RTB | AEEM | CERFI
source_typestring–youtube (harvested web video, the large majority) | deposited (recordings with a file, 47)
subjectstring–Exact subject tag — only ~27 rows carry one, so prefer publisher/keyword

No output schema declared.

No examples provided.

search_by_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.

NameTypeReqDescription
centralitystring–Très central | Central | Secondaire | Marginal | Non abordé
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
disputedstring–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.
limitinteger–Default 20, max 100
offsetinteger––
polaritystring–Très positif | Positif | Neutre | Négatif | Très négatif | Non applicable
subjectstring––
subjectivitystring–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 ~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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional). Corpus is mostly Burkina Faso/Togo/Benin
keywordstring–Concept keyword; every word must occur in the title, OCR, French/English AI descriptions or subject; "quote" a phrase
limitinteger–Default 15, max 50
offsetinteger––

No output schema declared.

No examples provided.

search_images ~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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional)
creatorstring–Photographer name (substring match)
date_fromstring–YYYY-MM-DD (or YYYY)
date_tostring–YYYY-MM-DD (or YYYY)
keywordstring–French concept keyword; every word must occur in the title, creator, subject, place or caption; "quote" a phrase
limitinteger–Default 20, max 50
offsetinteger––
spatialstring–Exact place name, e.g. Ouagadougou (pipe-aware)
subjectstring–Exact subject tag (pipe-aware)

No output schema declared.

No examples provided.

search_index ~137

Search the IWAC authority index (persons, places, organisations, events, subjects) by name. Accent/case-insensitive.

NameTypeReqDescription
index_typestring–Exact type (accents optional), validated against: Personnes | Lieux | Organisations | Événements | Sujets | Notices d'autorité. An unrecognised value returns an error listing the valid types.
keywordstringyesEvery word must occur in the entry title (any order); "quote" a phrase, or give a whole alternate title
limitinteger–Default 20, max 100
offsetinteger––

No output schema declared.

No examples provided.

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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
date_fromstring–Earliest year, YYYY
date_tostring–Latest year, YYYY
exactobject–AND values. Fields: subject/spatial/author/language/country/newspaper/topic_id/min_prob/scored_by; country_raw=whole cell; polarity:<model>.
hijri_monthstring–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_yearinteger–Islamic (Umm al-Qura) year, e.g. 1445
keywordstring–French concept keyword; every word must occur in the title, subject, table of contents or OCR; "quote" a phrase
keyword_aliasesarray––
keyword_modestring–literal: the whole keyword as one substring
limitinteger–Default 20, max 100
newspaperstring–Periodical/series title (see list_periodicals)
offsetinteger––
subjectstring–Subject tag (~87% of issues are tagged)

No output schema declared.

No examples provided.

search_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.

NameTypeReqDescription
authorstring––
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional)
date_fromstring–Earliest year, YYYY
date_tostring–Latest year, YYYY
keywordstring–French or English concept keyword; every word must occur in the title + abstract; "quote" a phrase
languagestring–e.g. Français | Anglais
limitinteger–Default 20, max 100
offsetinteger––
reference_typestring–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…
subjectstring–Subject tag (sparse: ~27% of references are tagged)

No output schema declared.

No examples provided.

semantic_search_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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
date_fromstring–YYYY-MM-DD (or YYYY)
date_tostring–YYYY-MM-DD (or YYYY)
limitinteger–Default 10, max 50
newspaperstring––
querystringyesNatural-language query, any language

No output schema declared.

No examples provided.

semantic_search_images ~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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional)
limitinteger–Default 10, max 30
querystringyesDescription of the visual content, any language

No output schema declared.

No examples provided.

semantic_search_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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Togo (accents optional)
limitinteger–Default 10, max 50
querystringyesNatural-language query, any language

No output schema declared.

No examples provided.

semantic_search_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.

NameTypeReqDescription
countrystring–Exact country name: Benin | Burkina Faso | Côte d'Ivoire | Niger | Nigeria | Togo (accents optional)
date_fromstring–Earliest year, YYYY
date_tostring–Latest year, YYYY
languagestring–e.g. Français | Anglais
limitinteger–Default 10, max 50
querystringyesNatural-language query, any language
reference_typestring–French type label, substring (e.g. Thèse de doctorat)

No output schema declared.

No examples provided.

Install

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

# add to Claude Code
claude mcp add --transport http fmadore-iwac-mcp-server 'https://islam.zmo.de/mcp/'
Common questions

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.