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anydocs

An MCP server that gives coding agents fast search over other tools' documentation — Claude Code, OpenAI Codex, Cursor, opencode, xAI, and whatever else you add.

Docs are ingested in CI, indexed into SQLite FTS5, and published as a release artifact. The server downloads it and serves five tools:

tool

what it does

search_docs

BM25-ranked hits as short snippets — never whole sections

read_doc

one page, or one heading section of it

grep_docs

regex over the raw markdown, for exact symbols BM25 splits

list_sources

which doc sets are indexed

list_pages

a source's pages and descriptions

A search costs ~500 tokens. Returning whole matched sections instead — the obvious way to build this — costs 10k+ for the same question. That gap is the reason anydocs exists.

Everything runs locally: no API key, no network at query time, no service to keep alive. The whole index is ~7 MB.

Install

Codex

Codex reads MCP servers from ~/.codex/config.toml or, for a trusted project, .codex/config.toml. Add it globally with the CLI:

codex mcp add anydocs -- \
  uvx --from git+https://github.com/kiyeonjeon21/anydocs anydocs
codex mcp list

Or use project configuration. The longer startup timeout covers the first cold uvx install and index download; required makes a broken server fail loudly.

[mcp_servers.anydocs]
command = "uvx"
args = [
  "--from",
  "git+https://github.com/kiyeonjeon21/anydocs",
  "anydocs",
]
startup_timeout_sec = 120
required = true

[mcp_servers.anydocs.env]
ANYDOCS_SOURCES = "codex"

Restart Codex after changing configuration. To make tool selection reliable, put this in the project's AGENTS.md:

When anydocs MCP is available, use search_docs with the product's source and
then read_doc before answering questions about that product's documentation.

Clients using .mcp.json

For clients that support .mcp.json, use the following. Nothing needs to be installed first: uvx fetches the server, and the server fetches the index on first run.

{
  "mcpServers": {
    "anydocs": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/kiyeonjeon21/anydocs",
        "anydocs"
      ]
    }
  }
}

Related MCP server: MCP Spark Documentation Server

Scoping a project to the docs it uses

ANYDOCS_SOURCES limits the server to the sources you name. The rest disappear — from list_sources, from the source enum the model sees, and from every tool, including direct read_doc calls.

Worth doing. These doc sets describe the same ideas in different words, so on a Claude Code repo an unfiltered search for hook events hands 3 of its 5 slots to Cursor and xAI.

{
  "mcpServers": {
    "anydocs": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/kiyeonjeon21/anydocs",
        "anydocs"
      ],
      "env": {
        "ANYDOCS_SOURCES": "claude-code,codex"
      }
    }
  }
}

In Codex config, the equivalent is:

[mcp_servers.anydocs.env]
ANYDOCS_SOURCES = "claude-code,codex"

Available: claude-code, codex, cursor, opencode, xai. A name that is not in the index stops the server and prints the valid ones, rather than quietly serving an empty index.

What it does not do

Matching is lexical, and the tools say so rather than bluffing:

  • English only. The docs are English and matching is by word, so a Korean or Japanese query reaches nothing. search_docs names the words it had to ignore instead of quietly answering a question you did not ask.

  • No fuzzy matching. A typo finds nothing. It is reported as a typo.

  • OR matching always finds something. Ask Claude Code's docs about cursorrules and the hits will be pages that merely contain tab. The reply says which of your words never reached the results, so a weak match cannot pass as an answer.

Embeddings were measured and left out: dense retrieval alone scored worse than BM25 on these corpora (hit@1 0.775 vs 0.804), and a hybrid moved recall@8 from 0.946 to 0.964 — five questions out of 276 — in exchange for a 130 MB model on every client or a server to keep running. Not worth it yet.

Adding a source

Drop a YAML file in sources/. Sites do not agree on how to publish docs, so there are three ingest strategies:

strategy

when

example

llms-txt

llms.txt is an index of pages, each with a .md twin

Claude Code, Codex

sitemap

no llms.txt — take the page list from sitemap.xml

Cursor, opencode

llms-full

llms.txt is the corpus, split by a delimiter

xAI

id: cursor
title: Cursor
tags: [coding-agent]
strategy: sitemap
entry: https://cursor.com/docs/sitemap.xml
base_url: https://cursor.com/docs/
page_suffix: .md
include: ["https://cursor.com/docs/*"]   # the sitemap carries 13 locales
expect_pages: 165                        # guards against the site moving

Two things to get right, both of which fail silently:

  • Locales. Every sitemap carries them, and they can multiply a source by 17. expect_pages is checked in both directions, so a filter that stops matching is a build failure rather than a quietly bloated index.

  • slug_style. Sites slug their heading anchors differently, and a wrong slug still ranks fine — it just lands in the wrong place, which nothing else would catch. collapse for Mintlify (CLAUDE.mdclaude-md), github for Astro Starlight (Avante.nvimavantenvim), verbatim for the rest. CI checks every anchor against the live HTML on each sync.

CI re-ingests daily and publishes a new index only when the docs actually changed.

Development

uv run anydocs-build                      # ingest + index into build/
uv run pytest -q
uv run python scripts/eval_search.py      # retrieval quality against a gold set
uv run python scripts/verify_anchors.py   # anchors resolve on the live sites
uv run python scripts/sweep_chunk.py      # re-chunk from pages.body, no refetch

A local build/ directory takes precedence over the published index, so anydocs-build then anydocs serves what you just built.

Retrieval changes need evidence. scripts/eval_search.py scores against a hand-written gold set plus 276 auto-derived questions (each page's llms.txt description, which is a paraphrase and is not among the indexed columns). A one-case swing on the hand set is noise; several plausible improvements died on these numbers.

License

MIT

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Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)
Commit activity

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