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Search coding agent docs locally with efficient indexing, page reading, and markdown grep.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "anydocs" yet — see the docs or source repo.
Search the indexed documentation for snippets related to Cursor configuration, and return the most relevant results with source pages.
Returns relevant documentation snippets with page references for deeper reading.
Open and read the documentation page about using Claude Code tools, and extract the main steps.
Provides a summary of the key information or steps from the page content.
Search all indexed markdown docs for occurrences of “authentication” or “API key” and list the matches.
Returns matching lines or snippets with document locations for quick navigation.
Developers using coding agents like Claude Code or Cursor can search for relevant documentation snippets first, then open the matching pages for full details, reducing manual browsing.
When you need to find a term, parameter name, or topic across many markdown files, grep-style search helps quickly locate all relevant occurrences.
For users who frequently query coding-agent documentation, this tool uses local SQLite FTS5 indexing to provide faster and more token-efficient search.
It is an MCP tool for fast, token-efficient local search over coding-agent documentation. Known capabilities include snippet search, page reading, and grep-style search across markdown files.
The original description says it uses local SQLite FTS5 indexing to support efficient documentation search. For more implementation details, see the source repository.
From the description, it targets coding-agent documentation and mentions Claude Code and Cursor as examples. For supported sources and exact integration details, see the source repository.
Generate, search, and maintain codebase documentation for faster team development.
Search codebases semantically and find relevant snippets with source locations.
Search indexed codebases semantically with natural language across MCP clients.
Lets coding agents search and retrieve real documentation through an MCP server.
Search code with natural language and get precise ranked file-line matches.
Crawl sites and repos into searchable Markdown for AI agents and local LLMs.