An MCP server that indexes codebases into a local graph and provides on-demand context retrieval for AI coding agents, reducing token usage by tracking session history and delivering only relevant code subgraphs.
An MCP server that provides AI coding agents with AST-accurate, context-budget-aware codebase querying, safety gates, and team policy integration via structured tools and a local plugin layer.
MCP server that reduces AI agent token usage by up to 90% through intelligent context compression. Enables efficient code exploration, multi-file refactoring, and debugging by providing tools for smart reading, searching, and managing code context.
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.
MCP server that helps AI coding agents understand a repository by providing lightweight tree/map, code search, and token-budgeted context packing tools without dumping the entire monorepo into the prompt.
