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fathom-mcp

fathom-mcp

by veer-mehta
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

docs-mcp

Documentation RAG system: crawl a docs site → chunk + embed locally (HuggingFace) → store in Postgres+pgvector → semantic search via MCP server, REST API, and web UI.

Demo

live at https://docs-mcp.veermehta.dev

Related MCP server: MCPDocSearch

Architecture

flowchart LR
    A[Browser] --> B[API Server]
    B --> D[Web UI]
    B --> C[(Postgres + pgvector)]
    B --> G[Ingestion Pipeline]
    G --> H[Scraper Subprocess]
    G --> C
    I[AI Client<br/>Claude Code, OpenCode] -->|MCP over stdio| F[MCP Server]
    F --> C

Quick start

git clone ... docs-mcp && cd docs-mcp
python -m venv .venv && source .venv/bin/activate
pip install -e ".[local]"
docker compose up -d
cp .env.example .env              # set LLM_API_KEY
.venv/bin/docs-mcp-api            # http://127.0.0.1:8000

MCP tools

add_documentation · estimate_documentation · search_documentation · list_sources · get_ingest_status · add_local_docs

REST API

Endpoint

What

GET /search?q=...

Semantic search

GET /sources

Indexed sources

POST /upload

Upload files

POST /upload-folder

Index a local folder

GET /llm-chat?q=...

Chat with docs

GET /about

System info

GET /docs

Interactive OpenAPI documentation

GET /openapi.json

OpenAPI schema

OpenCode

~/.config/opencode/opencode.jsonc:

{
  "mcp": {
    "docs-mcp": {
      "type": "local",
      "command": ["/path/to/docs-mcp/.venv/bin/python", "-m", "docs_mcp.mcp"]
    }
  }
}

verify it with:

echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}' | /path/to/docs-mcp/.venv/bin/python -m docs_mcp.mcp

Config

Copy .env.example to .env — set EMBEDDING_PROVIDER=api + EMBEDDING_API_KEY for remote embeddings (Jina, OpenAI, etc.), or leave as local for HuggingFace.

Available Tools

5 tools
add_documentationA

Crawl a framework/library documentation site and index it for semantic search.

Re-ingesting an existing source is incremental: pages whose extracted markdown is unchanged are skipped (no re-embedding).

Args: name: Short identifier for the framework, e.g. "react". version: Version string, e.g. "18.3" or "latest". base_url: Entry point URL of the documentation site. max_depth: How many link hops to follow from base_url. max_pages: Hard cap on the number of pages crawled. background: If true, start the crawl and return a job id immediately; track it with get_ingest_status. Large sites should use this to avoid tool timeouts. prune_missing: If true, delete indexed pages that this crawl did not visit. Only enable when depth/page caps cover the whole site, otherwise capped crawls would delete valid pages. lang: ISO 639-1 language code to filter pages (e.g. "en"). Only pages matching this language are crawled. sitemap: If true, discover pages from sitemap.xml instead of following links. Gives better coverage for docs sites that expose a sitemap.

Inputs: name (required), version (required), base_url (required), lang, +5 more. Returns: result

add_local_docsA

Index local documentation files from a folder on disk.

Walks the folder, finds supported files (HTML, Markdown, PDF, TXT), extracts text, chunks, embeds, and stores them for semantic search.

Args: name: Short identifier for this collection, e.g. "internal-api". path: Absolute or relative path to the folder on the server. recursive: If true, descend into subdirectories (default true).

Inputs: name (required), path (required), recursive. Returns: result

get_ingest_statusA

Check progress of a background add_documentation job.

Args: job_id: The id returned when the job was submitted with background=true.

Inputs: job_id (required). Returns: result

list_sourcesA

List all indexed documentation sources with page and chunk counts.

Inputs: no named parameters. Returns: result

search_documentationA

Semantic search over indexed documentation.

Returns the most relevant markdown chunks with their source URL and heading path. Use add_documentation first if nothing is indexed yet.

Args: query: What to look for, e.g. "how to define a loader". name: Optional framework name filter, e.g. "react". version: Optional version filter, e.g. "18.3". k: Number of chunks to return (1-20). mode: "hybrid" (default) fuses vector + keyword ranking; "vector" or "keyword" force a single strategy.

Inputs: query (required), k, mode, name, +1 more. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.2/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct operation: web ingestion (add_documentation), local ingestion (add_local_docs), job tracking (get_ingest_status), search (search_documentation), and enumeration (list_sources). The two ingest tools could superficially be confused, but their descriptions clearly separate web-crawl vs local-folder scopes.

    Naming Consistency5/5

    All tools use consistent snake_case verb_noun naming: add_documentation, add_local_docs, get_ingest_status, search_documentation, list_sources. The verb set (add/get/search/list) is predictable and readable throughout.

    Tool Count5/5

    Five tools is well-scoped for a documentation indexing/search server, covering ingestion, async job tracking, retrieval, and listing. No tool feels redundant or gratuitous.

    Completeness4/5

    The surface covers ingest (web + local), status, search, and list, which handles the core RAG lifecycle. However, there is no tool to delete or remove an indexed source, and no way to inspect job history or cancel a running job, leaving minor gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

    Resources

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