football-docs
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Searchable football data provider documentation for AI coding agents. Like Context7 for football data.
football-docs
Searchable football data provider documentation for AI coding agents. Like Context7 for football data.
Who it's for: Developers and analysts who use AI coding tools (Claude Code, Cursor, VS Code Copilot, Windsurf) to work with football data. Works with any tool that supports MCP.
What it does: Gives your AI agent a searchable index of documentation for 15 football data providers — event types, qualifier IDs, coordinate systems, API endpoints, data models, identity surfaces, and cross-provider comparisons. Your agent looks up the real docs instead of guessing from training data.
Why not just let the AI figure it out? LLMs get football data specifics wrong constantly — Opta qualifier IDs, StatsBomb coordinate ranges, API endpoint URLs, library method signatures. These are mutable facts that change across versions. football-docs gives the agent verified, sourced documentation with provenance tracking so you know where every answer came from.
Provider identity facts
football-docs is the public source for provider identity-surface facts: access
shape, ID schemes, matching fields, provider quirks, and provenance rules.
Curated Reep-derived notes belong here when they can be stated without private
register state. They should say whether a fact comes from public docs, public
page evidence, licensed feed shape, or a reviewed public-safe observation, and
must not include private paths, credentials, scraper state, action ledgers, mint
salts, or raw restricted payloads.
MCP (Model Context Protocol) is a standard for connecting AI coding tools to external data sources.
Quick start
Claude Code
claude mcp add football-docs -- npx -y football-docs
Cursor
Settings → MCP → Add server. Use this config:
{
"mcpServers": {
"football-docs": {
"command": "npx",
"args": ["-y", "football-docs"]
}
}
}
VS Code / Copilot
Add to .vscode/mcp.json:
{
"servers": {
"football-docs": {
"command": "npx",
"args": ["-y", "football-docs"]
}
}
}
Windsurf
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": {
"football-docs": {
"command": "npx",
"args": ["-y", "football-docs"]
}
}
}
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"football-docs": {
"command": "npx",
"args": ["-y", "football-docs"]
}
}
}
Tools
| Tool | Description |
|---|---|
search_docs |
Full-text search across all provider docs. Filter by provider. Results include provenance (source URL, version). |
list_providers |
List all indexed providers and their doc coverage. |
compare_providers |
Compare how different providers handle the same concept. |
request_update |
Request a new provider, flag outdated docs, or suggest a better doc source. Queued for maintainer review. |
Example queries
- "What is Opta qualifier 76?" (big chance)
- "How does StatsBomb represent shot events?"
- "Compare Opta and Wyscout coordinate systems"
- "Which provider IDs are safe identity bridges for Transfermarkt players?"
- "Does SportMonks have xG data?"
- "What event types does kloppy map to GenericEvent?"
- "How does SPADL represent a tackle?"
Indexed providers
| Provider | Chunks | Categories |
|---|---|---|
| StatsBomb | 150 | event-types, data-model, coordinate-system, api-access, xg-model, identity-surfaces |
| kloppy | 100 | data-model, usage, provider-mapping |
| SportMonks | 78 | event-types, data-model, api-access, identity-surfaces |
| databallpy | 63 | data-model, overview, usage |
| mplsoccer | 62 | overview, pitch-types, visualizations |
| Wyscout | 68 | event-types, data-model, coordinate-system, api-access, identity-surfaces |
| Free sources | 45 | overview, fbref, understat |
| soccerdata | 40 | overview, data-sources, usage |
| Opta | 36 | event-types, qualifiers, coordinate-system, api-access, identity-surfaces |
| socceraction | 26 | SPADL format, VAEP, Expected Threat |
| FotMob | 7 | identity-surfaces |
| Impect | 7 | identity-surfaces |
| SkillCorner | 7 | identity-surfaces |
| Soccerdonna | 7 | identity-surfaces |
| Transfermarkt | 7 | identity-surfaces |
703 searchable chunks across 15 providers.
Contributing
Contributions are welcome from everyone. There are three ways to help:
- Open an issue — request a new provider, flag outdated docs, or suggest a better doc source
- Use the
request_updatetool — AI agents can flag outdated or missing docs directly via the MCP server, which queues requests for maintainer review - Open a PR — fix errors, add new providers, or improve existing docs
You don't need to be an expert. See CONTRIBUTING.md for the full guide.
What we especially need
| Provider | Priority | Source material to start from |
|---|---|---|
| FPL (Fantasy Premier League) | High | FPL APIs Explained |
| API-Football (RapidAPI) | High | API-Football docs |
| Football-data.org | Medium | Football-data.org docs |
| TheSportsDB | Medium | TheSportsDB API |
| WhoScored | Medium | Based on Opta F24, community-documented |
| Sofascore | Medium | Unofficial API, community-documented |
For maintainers
Crawl pipeline
Provider doc sources are tracked in providers.json. The crawl pipeline discovers the best doc source (llms.txt > ReadTheDocs > GitHub README) and writes markdown with provenance frontmatter.
npm run discover # probe sources without crawling
npm run crawl # crawl all providers with sources
npm run crawl -- --provider kloppy # crawl one provider
npm run ingest # rebuild search index from docs/
npm run ingest -- --provider kloppy # re-ingest one provider (incremental)
Each crawled doc carries provenance metadata (source URL, source type, upstream version, crawl timestamp) that is surfaced in search results, so agents can distinguish between curated content and upstream documentation.
License
MIT
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