Skip to main content
Glama
FuryCow

memory_graph_mcp

by FuryCow
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Related Servers

Alternatives to memory_graph_mcp

No user-submitted related servers found.

    Related Servers

    • Simple Rick

      good-v1be
      A
      license
      Not graded
      quality
      C
      maintenance
      Provides AI coding agents with persistent memory by recording sessions and normalizing them into a searchable knowledge graph, then delivering relevant context at the start of the next session.
      MIT

    • hive-memory

      moonx010
      A
      license
      Not graded
      quality
      C
      maintenance
      Provides AI coding agents with persistent, graph-connected memory across projects, enabling cross-project context retrieval via synaptic connections and hybrid search.
      9 npm
      8
      MIT

    • agent-memory-mcp

      Yarmoluk
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables persistent, graph-based memory for AI agents, allowing them to store, traverse, and recall relationships between facts, decisions, and context across sessions for efficient reasoning and reduced token usage.
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.7/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool targets a distinct operation: recording a session, querying context, analyzing impact, inspecting side effects, and viewing stats. There is no meaningful overlap, so an agent can reliably pick the right tool.

    Naming Consistency4/5

    All tools share the graph_ prefix and most follow a verb_noun pattern, but graph_impact_analysis and graph_stats are noun-style names and only graph_get_side_effects uses 'get_'. The overall pattern is still predictable and readable.

    Tool Count5/5

    Five tools is a tight, well-scoped set that covers the server's apparent purpose without redundancy or bloat. Each tool earns its place.

    Completeness4/5

    The set covers the core workflows: recording new knowledge, querying relationships, assessing change impact, inspecting side effects, and checking index health. Minor gaps like updating or deleting sessions are absent but not critical to the primary graph-based workflow.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources