African Speech Corpora Quality Audit
PYPI · AFRICAN-SPEECH-MCP
Read-only, provenance-aware selection of Wolof speech corpora by measured quality.
Available components
Last scanned (23 hours ago)
Scores higher than 96% of PyPI servers
Category AI and Machine Learning
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security99
- No malware found by supply-chain analysis.Pass
- Known CVEs were checked across the 45 of 46 dependencies we could resolve, so this covers what we could see, not the whole tree.Partial
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- Dependency health was assessed across the 45 of 46 dependencies we could resolve, so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to papasega/african-speech-mcp). View diagnostics → Pass
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 68 days ago).Pass
- Security-disclosure policy not yet verified: we couldn't inspect the source repository.Unverified
Schema Quality & AI Usability72
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 555 tokens (~69/item across 8 items; 8 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage91
- 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 (100% 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 8 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 9 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
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.
- 3 Nov 26 0
- Security disclosure: fail → unverified ▼ functional
- 28 Oct 26 0
- Security disclosure: unverified → fail ▼ functional
- 26 Oct 26 0
- Security disclosure: fail → unverified ▼ functional
- 25 Oct 26 0
- Stability: 0.97 → pass security
- 24 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 23 Oct 26 −1
- Stability: pass → 0.93 functional
- 17 Oct 26 0
- Stability: 0.97 → pass security
- 16 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
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 · Analysed pypi/african-speech-mcp@2.0.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | papasega/african-speech-mcp |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/papasega/african-speech-mcp/.github/workflows/publish-pypi.yml@refs/heads/main |
| Rekor log index | 2614963900 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:66dbc5de65e1b97cf8e42ad84c73d18165f5098b3ff3893c9898ca0807fcbfca |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 45 packages
| Packages resolved | 45 |
|---|---|
| Stale | 5 |
| No linked repository | 1 |
| Tree resolution | Partial |
The dependency tree was only partially resolved, so these counts may be incomplete.
Background: SBOMs and build attestations, explained →
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 →
audit_corpus ~58
Return dated observed quality metrics separately from published figures. Missing observations remain null, never implicit zero.
| Name | Type | Req | Description |
|---|---|---|---|
| audit_id | – | – | Specific audit snapshot. |
| corpus | string | yes | Variant key. |
| include_published | boolean | – | Include source figures. |
| Name | Type | Req | Description |
|---|---|---|---|
| audit_id | – | – | – |
| audit_status | string | yes | – |
| citation | string | yes | – |
| commercial_use | – | yes | – |
| confidence | – | – | – |
| config | – | – | – |
| corpus | string | yes | – |
| counts | – | – | – |
| dataset_family | string | yes | – |
| domain | – | – | – |
| durations | – | – | – |
| language | string | yes | – |
| language_purity | – | – | – |
| licence | string | yes | – |
| measurement_method | – | – | – |
| observed_at | – | – | – |
| provenance | – | yes | – |
| published_metrics | – | – | – |
| quality_notes | – | – | – |
| source_reference | – | – | – |
| speakers | – | – | – |
| speech_type | – | – | – |
| split_scope | – | – | – |
| task | string | yes | – |
| verification_basis | – | – | – |
| warnings | array | – | – |
No examples provided.
cite_corpus ~28
Return licence and citations, including parents of derivatives.
| Name | Type | Req | Description |
|---|---|---|---|
| corpus | string | yes | Variant key. |
| Name | Type | Req | Description |
|---|---|---|---|
| also_cite | array | – | – |
| bibtex | string | yes | – |
| commercial_use | – | yes | – |
| homepage | string | yes | – |
| licence | string | yes | – |
| usage_note | string | – | – |
No examples provided.
compare_corpora ~29
Compare variant quality, provenance, licence and benchmark status.
| Name | Type | Req | Description |
|---|---|---|---|
| corpora | array | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| compared | integer | yes | – |
| corpora | array | yes | – |
| warnings | array | – | – |
No examples provided.
corpus_stats ~28
Return rows and schema for exactly one declared dataset configuration.
| Name | Type | Req | Description |
|---|---|---|---|
| corpus | string | yes | Variant key. |
| Name | Type | Req | Description |
|---|---|---|---|
| columns | array | yes | – |
| declared_splits | array | yes | – |
| observed_configs | array | – | – |
| provenance | – | yes | – |
| splits | array | yes | – |
| total_rows | integer | yes | – |
| undeclared_splits | array | – | – |
| warnings | array | – | – |
No examples provided.
filter_segments ~96
Filter rows only when a versioned row-level audit manifest exists; aggregated audit totals alone produce a structured refusal.
| Name | Type | Req | Description |
|---|---|---|---|
| corpus | string | yes | Variant key. |
| exclude_corrupt | boolean | – | – |
| exclude_duplicates | boolean | – | – |
| exclude_non_wolof | boolean | – | – |
| limit | integer | – | – |
| min_quality | – | – | Requested row quality. |
| query | – | – | – |
| split | – | – | Declared split. |
| Name | Type | Req | Description |
|---|---|---|---|
| audit_id | – | – | – |
| corpus | string | yes | – |
| filter_available | boolean | yes | – |
| manifest_path | – | – | – |
| provenance | – | yes | – |
| reason | string | yes | – |
| required_manifest_columns | array | yes | – |
| segments | array | – | – |
| warnings | array | – | – |
No examples provided.
list_corpora ~50
List language/task/config variants with audit and verification state.
| Name | Type | Req | Description |
|---|---|---|---|
| include_derivatives | boolean | – | Include derivatives. |
| language | – | – | ISO 639-3 filter. |
| task | – | – | Task filter. |
| Name | Type | Req | Description |
|---|---|---|---|
| audited_count | integer | yes | – |
| corpora | array | yes | – |
| derivatives_count | integer | yes | – |
| disclaimer | string | – | – |
| originals_count | integer | yes | – |
| queryable_count | integer | yes | – |
| total | integer | yes | – |
No examples provided.
plan_training_set ~137
Build a de-duplicated variant plan using published or dated audit metrics, with explicit quality, licence, benchmark and language-purity decisions.
| Name | Type | Req | Description |
|---|---|---|---|
| exclude_evaluation_sets | – | – | Deprecated compatibility alias for include_benchmarks. |
| include_benchmarks | boolean | – | Include evaluation benchmarks. |
| include_mixed_language | boolean | – | Opt in to known mixed-language variants. |
| include_tts_for_asr | boolean | – | Explicitly permit TTS variants in an ASR plan. |
| language | string | – | – |
| metric_source | – | – | Metric provenance. |
| quality | – | – | Minimum/selection quality. |
| task | – | – | Requested task. |
| Name | Type | Req | Description |
|---|---|---|---|
| assumed_valid_duration | – | – | – |
| citations | array | yes | – |
| excluded_derivatives | array | yes | – |
| excluded_variants | object | yes | – |
| expert_verified_duration | – | – | – |
| hours_unknown_for | array | – | – |
| include_benchmarks | boolean | yes | – |
| include_mixed_language | boolean | yes | – |
| include_tts_for_asr | boolean | yes | – |
| included | array | yes | – |
| language | string | yes | – |
| licences | array | yes | – |
| metric_source | string | yes | – |
| quality | string | yes | – |
| task | string | yes | – |
| total_duration | – | yes | – |
| total_hours_transcribed | number | yes | Compatibility alias for total_duration.hours_decimal. |
| warnings | array | – | – |
No examples provided.
search_segments ~74
Search a schema-verified variant. Config overrides cannot cross language boundaries; temporary audio URLs are explicitly marked ephemeral.
| Name | Type | Req | Description |
|---|---|---|---|
| config | – | – | Compatibility parameter; must equal the variant config. |
| corpus | string | yes | Variant key. |
| limit | integer | – | – |
| query | string | yes | – |
| split | – | – | Declared split. |
| Name | Type | Req | Description |
|---|---|---|---|
| filter_available | boolean | yes | – |
| provenance | – | yes | – |
| query | string | yes | – |
| returned | integer | yes | – |
| segments | array | yes | – |
| total_matches | – | – | – |
| warnings | array | – | – |
No examples provided.
How do I install the African Speech Corpora Quality Audit MCP server?
African Speech Corpora Quality Audit runs locally as a PyPI package, launched with uvx african-speech-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · african-speech-mcp
claude mcp add papasega-african-speech-corpora -- uvx african-speech-mcp
What is the African Speech Corpora Quality Audit MCP server?
African Speech Corpora Quality Audit is an MCP server listed in the public MCP registry as io.github.papasega/african-speech-corpora. Read-only, provenance-aware selection of Wolof speech corpora by measured quality. This page covers its PyPI package (african-speech-mcp).
Is the African Speech Corpora Quality Audit MCP server safe to use?
African Speech Corpora Quality Audit scores 93 out of 100 on VerifyMCP. Its build provenance is signed and verified. 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 African Speech Corpora Quality Audit MCP server expose?
African Speech Corpora Quality Audit exposes 8 tools: list_corpora, search_segments, corpus_stats, cite_corpus, audit_corpus, and 3 more. Their descriptions and schemas cost roughly 500 tokens of context every time the server is loaded.
Is the African Speech Corpora Quality Audit MCP server still maintained?
African Speech Corpora Quality Audit 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.
What licence is the African Speech Corpora Quality Audit MCP server under?
African Speech Corpora Quality Audit declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.