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Related Servers

Alternatives to Engraphy

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Self-hosted, local-first knowledge graph and memory server for AI agents. Enables agents to persist, recall, and organize knowledge through MCP with automatic distillation, deduplication, and cross-linking.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to store, search, and link typed knowledge entities such as memories, people, projects, tasks, and documents over a Streamable HTTP MCP endpoint. Combines hybrid BM25 and vector search with a knowledge graph, and separates short-lived session context from durable memory that future agents can trust.
      9
      AGPL 3.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      MCP server for a self-hostable typed knowledge graph, giving AI agents durable structured memory with typed nodes, links, and flexible payloads. Enables agents to bootstrap, manage, and evolve their ontology via MCP tools.
      3,047 npm
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides local-first persistent memory with a typed knowledge graph and bounded multi-hop retrieval via MCP, letting coding agents and local LLM systems store, search, and recall facts across sessions without hosted services or model dependencies.
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Persistent, semantically-searchable memory for AI agents using local PostgreSQL, pgvector, and Ollama embeddings, exposed via MCP with hybrid retrieval, knowledge graph, and auto-recall hook.
      3 npm
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      A local-first compiled knowledge graph MCP server that provides structured memory for AI agents with full-text search, vector embeddings, and timeline tracking.
      131 npm
      8
      MIT