Llmsdottxt

llms.txt will be how agents read docs -- so serve it to them natively, from the deps a project already has.

Auto-discover llms.txt from your deps. Docs your agent can read. Zero setup.

An MCP server that scans your project's dependency manifests, discovers each package's llms.txt documentation endpoint, indexes the content locally under ~/.llms.txt.d/, and serves it to AI coding agents over the Model Context Protocol.

Quickstart

uvx llmsdottxt-mcp scan      # index the current project's dependencies
uvx llmsdottxt-mcp status    # show indexed packages
uvx llmsdottxt-mcp serve     # start the MCP server on stdio
uvx llmsdottxt-mcp doctor    # diagnose paths, write access, registry connectivity

Add it to an MCP client (e.g. Claude Code) as a stdio server running llmsdottxt-mcp serve. Four ecosystems work end-to-end: Python (pyproject.toml, requirements.txt), Node (package.json), Rust (Cargo.toml), and Go (go.mod).

Known Limitations

• Pre-1.0: MCP tool names and response schemas may change.
• A package with no discoverable llms.txt is a miss -- there is no HTML-scraping fallback.
• Docs hosts behind an unsolvable bot challenge (Cloudflare, DataDome, Imperva, AWS WAF, Akamai, Sucuri) are reported as blocked, not indexed -- passing them needs a real browser.
• Python 3.14+ only.