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Related Servers

Alternatives to MIHAD

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides coding agents with structured planning, persistent project memory, automated verification, and safety permission controls through MCP tools, enabling better planning, context retention, self-checking, and guarded execution.
      5 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Provides AI coding agents with deterministic, attestable org memory via an MCP server, enabling automatic recall of relevant facts on every prompt, loss-proof capture of learnings, and curated promotion of verified facts to a tenant-isolated memory store.
      Apache 2.0
    • F
      license
      B
      quality
      B
      maintenance
      Provides AI coding agents with a hybrid cognitive memory engine that reduces token usage, prevents amnesia, detects repetitive error loops, and retrieves relevant code context through MCP.
      6
      -
    • A
      license
      A
      quality
      A
      maintenance
      MCP server that gives coding agents persistent, verified memory of codebase decisions, conventions, and skills, with evidence-based claims that are re-checked via git hooks and human-gated review. Enables memory search, propose/approve, chat harvesting, and critique across MCP-compatible tools.
      21
      108 npm
      1
      MIT
    • A
      license
      B
      quality
      A
      maintenance
      Enables AI coding agents and local LLMs to store and recall project memory, compact verbose logs, look up code symbols, create and rewind workspace snapshots, detect risky commands and loops, pack context optimally, and draft tokens through MCP tools.
      10
      1
      Apache 2.0

    TDQS

    A3.7/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct action on memory items: recall (read), propose (create), correct (invalidate), and report_outcome (feedback). Their purposes do not overlap, and the descriptions clearly delineate when to use each.

    Naming Consistency5/5

    All tools follow a consistent memory_<verb> snake_case pattern: memory_recall, memory_propose, memory_correct, memory_report_outcome. The convention is predictable and readable.

    Tool Count5/5

    Four tools is well-scoped for a persistent memory interface, covering the essential agent interactions without redundancy. Each tool earns its place in the memory lifecycle.

    Completeness4/5

    The set covers read, create, invalidate, and feedback, but lacks explicit update or delete operations. Agents can work around this by proposing new items and marking old ones as wrong, so the gap is minor.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues