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    🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.
    7
    MIT
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    license
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    quality
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    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
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    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
    108 PyPI
    4
    MIT
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    Enables AI coding assistants to automatically scan, store, and query API endpoints from codebases, providing instant lookup and semantic search to reduce context switching and token consumption.
    1
    MIT
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    An MCP server designed to assist with generating, converting, and translating Milvus SDK code by retrieving relevant documentation and snippets. It supports PyMilvus code generation, ORM-to-client conversion, and cross-language translation between Python, Java, Go, and other supported languages.
    2
    MIT
  • F
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    Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.
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    A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.
    34
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    A Model Context Protocol (MCP) server that provides a RAG (Retrieval Augmented Generation) tool with hybrid search capabilities combining vector similarity and keyword metadata search for code retrieval.
    47 PyPI
    42
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  • A
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    Enables semantic search through 1C codebase exports using local CPU-based RAG with sentence transformers and FAISS indexing. Supports fast XML file indexing and retrieval of 1C code with metadata parsing.
    11
    MIT
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    An intelligent codebase processing server that provides agentic RAG capabilities for code repositories, enabling semantic search and contextual understanding through self-evaluating retrieval loops.
    2
    MIT
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    maintenance
    Provides a local creator asset library MCP server that scans folders to catalog media files, batch-renames them, applies tags, tracks asset lineage between source and finished works, and offers keyword- and BGE-vector-based semantic search. It also lets other content-production MCP servers auto-register their generated outputs into the library for later retrieval and reuse.
    MIT
  • F
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    MCP server that provides secure read-only access to a local folder, enabling file listing, reading, semantic search (RAG), and indexing status via natural language, integrated with Claude Desktop and a custom agent loop.
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  • F
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    B
    maintenance
    Enables MCP clients to persist, recall, update, forget, and search agent memories over stdio, backed by Postgres with pgvector for vector search. Supports cross-session memory validation with per-operation latency and outcome logging.
    1
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    license
    A
    quality
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    maintenance
    An MCP server that gives an AI agent long-term memory it cannot read. VaultZero is a privacy-first memory vault: this package embeds and encrypts every memory on your machine before it is sent, so the server stores ciphertext and vectors and never holds a key.
    12
    2
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Local RAG system for Claude Code with hybrid search (semantic + BM25), cross-encoder reranking, markdown-aware chunking, and 12 MCP tools. Zero external servers, pure ONNX in-process.
    13
    525 PyPI
    302
    MIT
  • A
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    An MCP server that enables searching and retrieving ACL NLP conference papers from a Qdrant vector database using semantic search and structured filters like year, venue, and field of study.
    4
    MIT
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    Enables AI agents to interact with an embedded graph database (GrafeoDB) via the Model Context Protocol, providing tools for graph CRUD, GQL queries, full-text and vector search, and graph algorithms.
    23
    5
    Apache 2.0
  • A
    license
    A
    quality
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    maintenance
    A persistent memory layer for Claude Code agents: five MCP tools (recall, remember, session, distill, status) over a markdown vault, SQLite FTS5 and an optional self-hosted Hindsight vector store, so an agent remembers facts, decisions and corrections across sessions.
    5
    MIT