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Related Servers

Alternatives to Facthouse

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      A persistent, searchable memory layer for AI assistants, exposed as an MCP server. It supports CRUD, namespaces, hybrid ranked search, relationships, chat-context assembly, import/export, and optional LLM-powered auto-extraction.
      3 npm
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Open-source MCP memory server providing persistent, cross-platform context for AI tools via a knowledge graph with encrypted storage.
      1 npm
      13
      AGPL 3.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      A self-hosted MCP server that provides a personal semantic memory layer for AI tools. It enables storing, searching, and managing memories using hybrid vector and keyword search, allowing AI assistants to recall information by meaning.
      MIT

    TDQS

    A4.4/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool maps to a distinct operation: raw event logging, durable fact capture, consolidation, statistics, session context, and retrieval/search. The three retrieval tools have clearly described boundaries, with get_entity for named things, get_context for broader relationship traversal, and search_knowledge for ranked fact lookup.

    Naming Consistency4/5

    The naming is mostly consistent: get_* for reads and verb_noun combinations for writes like capture_fact and log_event. Minor deviations are search_knowledge, which uses search_ instead of get_, and consolidate, which lacks a noun object.

    Tool Count5/5

    10 tools is well-scoped for a persistent knowledge and memory server. Capture, logging, consolidation, retrieval, stats, schemas, and session context each serve a distinct purpose without feeling padded or redundant.

    Completeness4/5

    The core memory lifecycle is covered: capture/log events, consolidate and reconcile facts, search and retrieve knowledge, inspect stats and schemas, and load session context. The main gap is the lack of an explicit forget/delete or manual fact-editing tool; corrections appear to rely on capturing contradictions and letting consolidation handle them.

    Maintenance

    ActivityActive
    ResponsivenessResponsive