tenequm/llms-txt-mcp

llms-txt-mcp

Fast, surgical access to big docs in Claude Code via llms.txt. Search first, fetch only what matters.

Why this exists

• Hitting token limits and timeouts on huge llms.txt files hurts flow and drowns context.
• This MCP keeps responses tiny and relevant. No dumps, no noise — just the parts you asked for.

Quick start (Claude Desktop)

Add to ~/Library/Application Support/Claude/claude_desktop_config.json or .mcp.json in your project:

{
  "mcpServers": {
    "llms-txt-mcp": {
      "command": "uvx",
      "args": [
        "llms-txt-mcp",
        "https://ai-sdk.dev/llms.txt",
        "https://nextjs.org/docs/llms.txt",
        "https://orm.drizzle.team/llms.txt"
      ]
    }
  }
}

Now Claude Code|Desktop can instantly search and retrieve exactly what it needs from those docs.

How it works

URL → Parse YAML/Markdown → Embed → Search → Get Section

• Parses multiple llms.txt formats (YAML frontmatter + Markdown)
• Embeds sections and searches semantically
• Retrieves only the top matches with a byte cap (default: 75KB)

Features

• Instant startup with lazy loading and background indexing
• Search-first; no full-document dumps
• Byte-capped responses to protect context windows
• Human-readable IDs (e.g. https://ai-sdk.dev/llms.txt#rag-agent)

Source resolution and crawling behavior

• Always checks for llms-full.txt first, even when llms.txt is configured. If present, it uses llms-full.txt for richer structure.
• For a plain llms.txt that only lists links, it indexes those links in the collection but does not crawl or scrape the pages behind them. Link-following/scraping may be added later.

Talk to it in Claude Code|Desktop

• "Search Next.js docs for middleware routing. Give only the most relevant sections and keep it under 60 KB."
• "From Drizzle ORM docs, show how to define relations. Retrieve the exact section content."
• "List which sources are indexed right now."
• "Refresh the Drizzle docs so I get the latest version, then search for migrations."
• "Get the section for app router dynamic routes from Next.js using its canonical ID."

Configuration (optional)

• --store-path PATH (default: none) Absolute path to persist embeddings. If set, disk persistence is enabled automatically. Prefer absolute paths (e.g., /Users/you/.llms-cache).

• --ttl DURATION (default: 24h) Refresh cadence for sources. Supports 30m, 24h, 7d.

• --timeout SECONDS (default: 30) HTTP timeout.

• --embed-model MODEL (default: BAAI/bge-small-en-v1.5) SentenceTransformers model id.

• --max-get-bytes N (default: 75000) Byte cap for retrieved content.

• --auto-retrieve-threshold FLOAT (default: 0.1) Score threshold (0–1) to auto-retrieve matches.

• --auto-retrieve-limit N (default: 5) Max docs to auto-retrieve per query.

• --no-preindex (default: off) Disable automatic pre-indexing on launch.

• --no-background-preindex (default: off) If preindexing is on, wait for it to finish before serving.

• --no-snippets (default: off) Disable content snippets in search results.

• --sources ... / positional sources One or more llms.txt or llms-full.txt URLs.

• --store {memory|disk} (default: auto) Not usually needed. Auto-selected based on --store-path. Use only to explicitly override behavior.

Development

make install  # install deps
make test     # run tests
make check    # format check, lint, type-check, tests
make fix      # auto-format and fix lint

Built on FastMCP and the Model Context Protocol. MIT license — see LICENSE.