Quality-aware, read-only MCP server for discovering and selecting African speech corpora, Wolof first, with audited metrics, provenance, licensing, and training-set planning.
# African Speech Corpora MCP
A read-only server implementing the Model Context Protocol, an open standard created by Anthropic, over public speech corpora for African languages: Wolof first, plus Pulaar and Sereer.
The project is **Wolof-first**. The 2.0 catalog contains 14 variants: 11 variants of original sources and 3 derivatives. Pulaar (`ful`) and Sereer (`srr`) are represented only by Kallaama variants without local metrics; the project does not claim Swahili or Amharic coverage. The bundled validation lock, generated on August 26, 2026, makes 6 Hugging Face variants queryable. A later validation run may naturally produce a different state.
Version 2.0.0 is distributed on PyPI and published as `io.github.papasega/african-speech-corpora` in the official MCP Registry.
The server does not train models, download complete corpora, or write to Hugging Face, OpenSLR, Kaggle, GitHub, or any other remote source.
## What the server measures
The quality pipeline keeps the following stages separate:
```text
raw audio → usable audio → transcribed audio → audit-accepted audio → expert-verified audio
```
- **Raw**: a file present in the observed snapshot.
- **Usable**: a file remaining after the audit's quantifiable exclusions.
- **Transcribed**: audio associated with a transcription.
- **Audit accepted**: an explicitly named union of expert-verified material and material only assumed valid by the audit.
- **Expert verified**: only `expert_audited` or `source_reported_expert`. An “a priori” assessment never enters this level.
Seconds are the canonical duration representation. Decimal hours and `HH:MM:SS` strings are derived at serialization time. Every audited metric states its scope, source, method, observation date, and confidence. A missing value remains `null`; it is never converted to zero. Figures published by a project remain under `published_metrics`, separate from local observations.
## 2026 Wolof snapshot
The machine-readable source is `assets/wolof- …