A local RAG-powered documentation search system that uses vector embeddings and Qdrant to enable semantic search across markdown, HTML, and other file formats. It provides an MCP interface for AI tools like Cursor to intelligently query and retrieve information from local knowledge bases.
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A local RAG-powered documentation search system that uses vector embeddings and Qdrant to enable semantic search across markdown, HTML, and other file formats. It provides an MCP interface for AI tools like Cursor to intelligently query and retrieve information from local knowledge bases.
Yes, local_lense is completely free to use with no usage limits on the free tier.
local_lense is listed under the search category in the AgentForge MCP registry.
local_lense has a current uptime of 99.9% with an average response time of 0ms.
To connect local_lense, click the "Connect Agent" button on this page to get the configuration snippet. Add it to your MCP client (Claude Desktop, Cursor, or any MCP-compatible tool). Your AI agent will then have access to all of local_lense's tools via the Model Context Protocol.