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"MCP to Enable Agents to Use OpenRouter or Google Vertex API" matching MCP servers:

  • 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

  • Similarity Search MCP Server

    nexus-mcp-infra
    F
    license
    -
    quality
    B
    maintenance
    Enables stateless similarity search over pre-computed vector corpora using NMI and cosine fusion with entropy-calibrated weighting. Provides tools for ranking, scoring, outlier detection, and alpha calibration for AI agents.

  • Munin AI Memory

    3d-era
    F
    license
    -
    quality
    B
    maintenance
    Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic
    3

  • Azure AI Agent Service + Azure

    0lovesakura0
    F
    license
    -
    quality
    D
    maintenance
    Enables Claude Desktop to search private documents using Azure AI Search and perform web searches with Bing, providing AI-enhanced results with source citations through Azure AI Agent Service or direct Azure AI Search integration.

  • Context MCP

    Raunak-dev-18
    A
    license
    A
    quality
    D
    maintenance
    Provides persistent context management for AI agents by storing and querying semantic information using Upstash Vector DB and Google AI embeddings. It enables semantic search, batch operations, and metadata filtering to help agents retrieve relevant stored knowledge.
    6
    3
    MIT

  • Mnemosyne MCP

    zhadyz
    A
    license
    B
    quality
    D
    maintenance
    Provides persistent knowledge graph memory for AI agents with local semantic search using Neo4j and ONNX embeddings, enabling offline operation with zero API costs.
    17
    17
    MIT
  • @vectros-ai/mcp-server by vectros-ai

    @vectros-ai/mcp-serverofficial

    vectros-ai
    A
    license
    -
    quality
    A
    maintenance
    MCP server for Vectros, a typed multi-tenant record store with hybrid search and citation-grounded RAG, enabling agents to query, search, and ask questions over their own indexed data.
    345
    1
    Apache 2.0
  • tigergraph-mcp by tigergraph

    tigergraph-mcpofficial

    tigergraph
    A
    license
    -
    quality
    B
    maintenance
    Model Context Protocol (MCP) server for TigerGraph that lets AI agents interact with TigerGraph through the MCP standard using pyTigerGraph's async APIs.
    3
    Apache 2.0

  • 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 Memory

    aiwithbenefits
    A
    license
    -
    quality
    D
    maintenance
    An MCP server that gives AI assistants the ability to remember user information (preferences, behaviors) across conversations using vector search technology.
    15
    MIT

  • n8n-fabric

    ry-ops
    A
    license
    -
    quality
    D
    maintenance
    Wraps n8n with an MCP server and vector storage to enable semantic search, management, and execution of automated workflows. It integrates with other tools to make workflows searchable and orchestratable within a larger automation ecosystem.
    1
    MIT

  • Markdown RAG

    ashrobertsdragon
    A
    license
    -
    quality
    D
    maintenance
    A Retrieval Augmented Generation system that enables AI assistants to perform semantic searches and manage document indices for markdown files. It supports PostgreSQL with pgvector and integrates both Google Gemini and Ollama for intelligent embedding generation.
    1
    MIT