Skip to main content
Glama

Related Servers

Alternatives to Fix Memory MCP

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
      A
      maintenance
      Local-first memory layer for AI coding agents — captures issues, attempts, fixes, and decisions, and warns at git commit before you repeat a mistake.
      17
      330 PyPI
      833
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      A persistent, local memory layer for AI coding agents that remembers decisions, bugs, and rules across sessions with three core MCP verbs (recall, remember, search).
      Apache 2.0
    • A
      license
      A
      quality
      A
      maintenance
      Persistent memory for AI coding agents, storing learned architecture decisions, patterns, and bug fixes in a local SQLite database with full-text search, enabling agents to recall information across sessions.
      6
      90 npm
      1
      MIT
    • A
      license
      A
      quality
      F
      maintenance
      Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.
      8
      2
      Apache 2.0

    TDQS

    C2.7/5.0

    Scored across 3 tools

    Disambiguation4/5

    The tools target distinct aspects: context assembly, general memory management, and lifecycle maintenance. However, manage_memory and maintain_memory_lifecycle could be confused due to overlapping scope, though descriptions help separate them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case (assemble_context, manage_memory, maintain_memory_lifecycle), making the naming predictable and uniform.

    Tool Count5/5

    With only 3 tools, the server is well-scoped and concise, covering context assembly, memory management, and lifecycle operations without unnecessary bloat.

    Completeness4/5

    The toolset covers the core memory lifecycle: assembling context, managing memory, and performing maintenance/recovery. Minor gaps like explicit search or list operations may exist, but manage_memory likely encompasses them.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues