Skip to main content
Glama
CreedLab

LogicMem MCP Server

by CreedLab
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Related Servers

Alternatives to LogicMem MCP Server

No user-submitted related servers found.

    Related Servers

    • Memclaw

      caura-ai
      A
      license
      Not graded
      quality
      A
      maintenance
      Governed shared memory platform for AI agents and agent fleets. Provides persistent memory, cross-agent knowledge sharing, permissions, audit trails, and multi-tenant isolation through a Model Context Protocol (MCP) server.
      4 npm
      538
      Apache 2.0

    • MAPI

      cabo0m
      A
      license
      Not graded
      quality
      D
      maintenance
      An auditable memory, lifecycle, and governance server for AI agents, providing durable memories with provenance, lifecycle management, and guarded workflows through the Model Context Protocol.
      Apache 2.0

    • @vemdev/mcp-server

      vem-dev
      A
      license
      Not graded
      quality
      D
      maintenance
      Gives AI agents durable project memory via the Model Context Protocol, allowing them to read tasks, record decisions, search context, and sync snapshots to the cloud.
      10 npm
      MIT

    • codebase-memory

      yuga-hashimoto
      A
      license
      Not graded
      quality
      D
      maintenance
      Provides persistent memory for AI coding agents through the Model Context Protocol, enabling them to store and retrieve project knowledge across sessions.
      22 npm
      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

    B3.2/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool targets a distinct operation: memory log, recall, session, stats, health, outcome, and reflect are all clearly differentiated. The A2A tools (register, heartbeat, list, write_shared, sync) also have distinct purposes with no overlap.

    Naming Consistency4/5

    All tools follow a consistent 'logicmem_<domain>_<action>' pattern using snake_case. Minor inconsistency arises because the final token is sometimes a noun (session, stats, health) and sometimes a verb (log, recall, reflect), but the overall structure is predictable and readable.

    Tool Count5/5

    12 tools is well within the ideal 3-15 range. The set covers two clear domains (memory management and A2A communication) with each tool serving a specific function, making the count feel appropriate and not bloated.

    Completeness4/5

    The memory lifecycle is well covered with store, search, full session briefing, stats, health, outcome feedback, and reflection. Minor gaps exist like missing memory update/delete and A2A deregistration, but these are not critical for the core workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources