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.
An MCP server that indexes codebases into a queryable knowledge graph, enabling agents to answer structural questions like callers, callees, dependencies, and impact analysis through tools like callers, callees, deps, search, and impact.
MCP server that enables coding agents to retrieve project context, semantically search indexed documentation, and read specific documents from registered repositories.
An MCP server that indexes reference repositories and provides tools for AI coding agents to retrieve lossless code context, enabling reasoning over codebases larger than the agent's context window.
An MCP server that provides structural codebase indexing and surgical query tools to drastically reduce token usage through symbol-level searches and transitive impact analysis. It supports multiple languages and integrates with git to help AI agents understand code dependencies and the impact of changes in sub-millisecond time.
