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"Learning to Create an Expert Python Program to Exit GitHub" matching MCP servers:

  • MCP PDF to PGVector

    sanskritiparmendranaval
    F
    license
    -
    quality
    C
    maintenance
    MCP server that ingests PDF documents into pgvector for semantic search and RAG pipelines. It handles extraction, chunking, local embeddings, and storage, enabling agents to make PDFs searchable via natural language.

  • Prompt Learning MCP Server

    curiositech
    F
    license
    -
    quality
    D
    maintenance
    Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.
    4

  • Tiny Chat

    to-aoki
    A
    license
    D
    quality
    C
    maintenance
    A lightweight RAG system that provides an MCP server for searching and interacting with vector-based knowledge bases. It enables users to perform retrieval-augmented generation and search across Qdrant collections through a standardized interface.
    1
    2
    MIT
  • Baidu Vector Database MCP Server by baidu

    Baidu Vector Database MCPofficial

    baidu
    A
    license
    B
    quality
    D
    maintenance
    A server that provides access to Baidu Cloud Vector Database functionality through the Model Context Protocol, enabling LLM applications to perform vector searches and database operations via natural language.
    14
    3
    Apache 2.0

  • semantic-code-mcp

    vrppaul
    F
    license
    A
    quality
    C
    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
    3

  • askDB

    RaviSenjaliya
    F
    license
    A
    quality
    C
    maintenance
    askDB is an MCP server that retrieves relevant database schema (DDL) from a Pinecone index and provides it to LLMs to write SQL, without connecting to the database itself.
    3

  • w3-mcp-server-qdrant

    famtong8-dev
    A
    license
    A
    quality
    C
    maintenance
    Python MCP server for vector search using Qdrant vector database and Ollama embeddings, with advanced query techniques like query expansion, HyDE, and reranking.
    2
    2
    MIT
  • Chroma MCP Server by chroma-core

    Chroma MCP Serverofficial

    chroma-core
    A
    license
    A
    quality
    D
    maintenance
    A server that provides data retrieval capabilities powered by Chroma embedding database, enabling AI models to create collections over generated data and user inputs, and retrieve that data using vector search, full text search, and metadata filtering.
    13
    585
    Apache 2.0

  • @rosalinddb/mcp

    rosalinddb
    A
    license
    A
    quality
    A
    maintenance
    Model Context Protocol server for RosalindDB, enabling AI clients to create datasets, ingest vectors, run similarity queries, and check usage on a cost-optimized vector search database.
    11
    16
    Apache 2.0

  • Chroma MCP Server

    zwczwczwc
    A
    license
    A
    quality
    C
    maintenance
    A Model Context Protocol server for Chroma, enabling AI models to create collections and retrieve data using vector search, full text search, and metadata filtering.
    13
    Apache 2.0
  • Zilliz MCP Server by zilliztech

    Zilliz MCP Serverofficial

    zilliztech
    A
    license
    A
    quality
    D
    maintenance
    Enables AI agents to interact with Milvus vector databases and Zilliz Cloud through natural language, allowing users to create clusters, manage collections, insert vector data, and perform semantic searches directly from their AI assistants.
    16
    34
    Apache 2.0

  • CoderSwap MCP Server

    njlnaet
    F
    license
    A
    quality
    -
    maintenance
    Enables AI agents to autonomously create and manage topic-specific vector knowledge bases with end-to-end functionality including project creation, content ingestion from URLs, semantic search, and progress tracking. Provides a complete research workflow without exposing low-level APIs.
    8
    93