Skip to main content
Glama
72,114 servers. Updated

Matching MCP tools:

"Ollama" matching MCP servers:

  • A
    license
    A
    quality
    A
    maintenance
    Long-term and multimodal memory for AI agents. Store facts and conversations with add_memory, recall them with search_memories — 8 tools over stdio/SSE/HTTP. Per-character memory isolation, LLM-based semantic deduplication, FAISS + JSON storage, and a fully local option (Ollama, no API key). Drop-in compatible with Mem0.
    8
    478
    Apache 2.0
  • A
    license
    A
    quality
    C
    maintenance
    Self-hosted Mem0 MCP server integrating Qdrant, Neo4j, and Ollama for semantic memory search, graph entity relationships, and memory management via OpenMemory API.
    6
    3
    MIT
  • F
    license
    A
    quality
    D
    maintenance
    Enables AI agents to query a local knowledge graph built from document collections using hybrid search (BM25 + vector fusion) and entity-relationship extraction. Supports privacy-first, offline operation with tools for semantic search, entity graph exploration, and corpus statistics.
    3
  • 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
  • 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
  • A
    license
    A
    quality
    A
    maintenance
    Self-hosted mem0 MCP server for Claude Code that adds durable async ingestion, document support, and reranking, enabling persistent memory management with Qdrant, Neo4j, and Ollama.
    15
    1
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Enables indexing and semantic search of codebases and documents via MCP, using Ollama embeddings and Qdrant vector store.
    5
    Apache 2.0
  • A
    license
    A
    quality
    D
    maintenance
    Provides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.
    4
    15
    MIT
  • A
    license
    B
    quality
    C
    maintenance
    Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.
    5
    18
    MIT
  • A
    license
    -
    quality
    -
    maintenance
    An MCP server that bridges local Ollama models and ChromaDB vector memory to MCP clients like Claude Code. It enables local text generation, vision-based image analysis, and semantic memory storage without requiring external API keys.
  • 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
  • A
    license
    -
    quality
    D
    maintenance
    A local RAG MCP server that enables AI tools like Claude to search indexed codebases and documentation using vector search with Ollama models.
    Apache 2.0