An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.
MCP server that enables coding agents to retrieve project context, semantically search indexed documentation, and read specific documents from registered repositories.
A local MCP server that provides AI coding assistants with semantic search capabilities over codebases. It indexes code using local embeddings and exposes tools for efficient code retrieval, saving tokens and improving response quality.
MCP server for semantic code indexing using vector embeddings, enabling AI agents to maintain persistent memory of codebases through natural language queries and intelligent chunking.
An MCP server that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
