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  • F
    license
    Not graded
    quality
    C
    maintenance
    MCP server for a modular RAG system that enables natural language question answering over enterprise documents with intent-aware routing, adaptive retrieval, and citation-backed responses.
    -
  • F
    license
    A
    quality
    D
    maintenance
    A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
    3
    4
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  • A
    license
    A
    quality
    D
    maintenance
    Enables semantic search over codebases using natural language queries, returning relevant code snippets with source locations. Integrates with Claude Code for automatic codebase exploration.
    1
    41 PyPI
    1
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.
    8
    65 PyPI
    MIT
  • A
    license
    A
    quality
    B
    maintenance
    Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.
    6
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Provides AI clients with a persistent, readable and writable long-term memory layer over MCP, enabling creation, retrieval, tagging, updating, and deletion of memories across sessions.
    49 npm
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Enables coding agents to find code by what it does rather than what it's called, searching local projects and remote GitHub or Bitbucket repositories all at once. Indexing and semantic search run fully offline with a locally loaded model, so code never leaves the machine.
    268 PyPI
    Apache 2.0
  • A
    license
    Not graded
    quality
    A
    maintenance
    Enables semantic code search across indexed codebases using natural language queries, with support for CLI and MCP interfaces.
    1
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables semantic code search across indexed code folders using vector embeddings, with support for multiple embedding providers and automatic file watching. Provides an admin UI and integrates with MCP clients for natural language code queries.
    1
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Turns a codebase into a queryable graph with semantic search, call graphs, and control/data flow analysis, served to AI coding agents via the Model Context Protocol.
    100 npm
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables Claude Desktop to retrieve only the most relevant sections from locally indexed documents, reducing context-window and token usage during conversations. Indexing and search run entirely on the user's machine using SQLite FTS5, with no network connection or telemetry.
    1
    MIT
  • F
    license
    Not graded
    quality
    C
    maintenance
    Transforms code repositories and development documentation into a queryable Neo4j knowledge graph, enabling AI assistants to perform intelligent code analysis, dependency mapping, impact assessment, and automated documentation generation across 15+ programming languages.
    7
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  • F
    license
    Not graded
    quality
    D
    maintenance
    Enables Claude to intelligently analyze and query codebases using knowledge graphs, supporting natural language code search, relationship discovery, and incremental updates.
    11
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  • F
    license
    Not graded
    quality
    B
    maintenance
    Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.
    4
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