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"Methods to Improve or Enhance a Prompt" matching MCP servers:

  • 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

  • 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.

  • 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

  • job-search-mcp

    jsundquist
    F
    license
    A
    quality
    B
    maintenance
    An MCP server that retrieves resume/experience evidence relevant to a job description via vector RAG, and tracks fit-analysis results in a configurable tracking store (Notion or SQLite), with tools like match_job, push_to_tracker, and list_applications.
    3

  • xgmem

    meetdhanani17
    A
    license
    A
    quality
    D
    maintenance
    A TypeScript-based MCP server that provides project-specific knowledge graph memory for LLM agents to store and retrieve entities, relations, and observations. It features disk-persistent storage and supports cross-project knowledge sharing to enhance agent long-term memory.
    14
    8
    7
    MIT
  • @manasdb/mcp-server by manasdb

    @manasdb/mcp-serverofficial

    manasdb
    A
    license
    -
    quality
    D
    maintenance
    Provides a plug-and-play persistent memory layer for MCP-compatible AI assistants, enabling them to store, retrieve, and delete memories across multiple databases simultaneously using semantic vector search.
    15
    MIT
  • MCP MariaDB Server by MariaDB

    MCP MariaDB Serverofficial

    MariaDB
    A
    license
    -
    quality
    C
    maintenance
    An interface for managing and querying MariaDB databases that supports standard SQL operations alongside advanced vector and embedding-based search capabilities. It enables AI assistants to seamlessly integrate relational and vector data workflows through a standardized protocol.
    189
    MIT

  • Tea Rags MCP

    artk0de
    A
    license
    -
    quality
    A
    maintenance
    A high-performance MCP server for semantic search and codebase indexing using the Qdrant vector database. It features optimized embedding pipelines, AST-aware chunking, and git metadata enrichment for fast, privacy-focused local or remote search.
    685
    11
    MIT

  • MCP Codebase Insight

    tosin2013
    A
    license
    -
    quality
    D
    maintenance
    A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.
    12
    MIT

  • MCP MariaDB Server

    Diae-Louali
    A
    license
    -
    quality
    D
    maintenance
    Enables AI assistants to interact with MariaDB databases through standard SQL operations and advanced vector/embedding-based search. Supports database management, schema inspection, and semantic document storage and retrieval with multiple embedding providers.
    MIT

  • mcp-rag-mini

    Pinger1456
    A
    license
    -
    quality
    B
    maintenance
    A minimal RAG service that exposes a vector index for document retrieval via REST and MCP, allowing querying for relevant document chunks and returning a suggested LLM prompt.
    MIT

  • GraphRAG MCP Server

    rileylemm
    A
    license
    -
    quality
    D
    maintenance
    Enables querying a hybrid system that combines Neo4j graph database and Qdrant vector database for powerful semantic and graph-based document retrieval through the Model Context Protocol.
    63
    MIT