Skip to main content
Glama
75,955 servers. Updated

Matching MCP tools:

Matching MCP Connectors:

"PostHog: Open-source product analytics platform" matching MCP servers:

  • A
    license
    Not graded
    quality
    B
    maintenance
    A self-hosted second brain MCP server that enables capturing thoughts with deduplication and semantic search using local embeddings and PostgreSQL with pgvector, all running on your own hardware.
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables querying live Zora token data and analytics methodology through SQL and document retrieval tools, providing guarded access to on-chain holder, transfer, and token information.
    MIT
  • A
    license
    A
    quality
    A
    maintenance
    Local-first, source-traceable memory for AI agents — no LLM at ingest, $0 per message, zero data egress. Gives Claude Code, Cursor, and any MCP client one shared persistent memory with semantic recall, belief revision, selective forgetting, and a provenance guard that blocks acting on stale or unconfirmed memories.
    23
    12
    MIT
  • A
    license
    B
    quality
    B
    maintenance
    Local-first knowledge retrieval MCP server that turns private text documents into a source-backed knowledge base, enabling retrieval, comparison, summaries, and review outlines for any local MCP client while keeping source paths and index operations visible.
    12
    1
    MIT
  • A
    license
    Not graded
    quality
    B
    maintenance
    Mem0-compatible persistent memory for AI agents - write facts once, recall them semantically in any session. Self-hostable open-source server, or managed cloud with a remote MCP endpoint at https://deepmem.dev/mcp.
    29
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server integration that creates a persistent, searchable working memory for AI-assisted development by enabling automated context recall and knowledge persistence in Chroma, the open-source embedding database.
    25
    MIT
  • A
    license
    Not graded
    quality
    A
    maintenance
    Open-source MCP server that gives any LLM long-term memory using a knowledge graph and vector search hybrid. It stores entities, observations, and relationships, enabling semantic recall across sessions with automatic clustering and fail-loud infrastructure.
    50
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Retrieval-only MCP server that turns any knowledge source (Obsidian vault, notes, reference sets) into searchable Qdrant-backed skills, exposing list_skills, search_vault, and search_skill tools for agents to query via stdio or SSE.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Enables intelligent search and question-answering over PDF documents using semantic similarity and keyword search. Supports OCR for scanned PDFs, persistent vector storage with ChromaDB, and maintains source tracking with page numbers.
    5
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Open-source MCP servers for ESG data extraction, analysis, and regulation management, providing 31 tools across 6 servers for tasks like metrics extraction, PDF processing, vector storage, and web scraping.
    MIT
  • F
    license
    Not graded
    quality
    D
    maintenance
    Enables AI-powered semantic search and question-answering for LiveKit documentation using Pinecone vector search and real-time web search with Tavily, providing detailed responses with source attribution.
  • F
    license
    Not graded
    quality
    D
    maintenance
    A multi-functional computing platform server designed to integrate with large language models like Qwen, providing file access, database connections, API integration, and vector database functionality.
    3
  • F
    license
    Not graded
    quality
    D
    maintenance
    An institutional-grade algorithmic trading platform that bridges MetaTrader 5 with an autonomous AI cortex for high-frequency data extraction, ML-driven analysis, and autonomous decision-making using the FEAT methodology.