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Related Servers

Alternatives to Product Memory

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Provides a shared local memory MCP server so multiple coding agents can store, retrieve, and attribute memories across sessions. It enables agents to recall project knowledge and past fixes with provenance.
      4
      Apache 2.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      MCP server that captures and recalls coding session memory (failures, decisions, diffs) for AI agents, enabling cross-agent continuity and preventing repeated mistakes.
      68 npm
      MIT
    • 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
      294 npm
      1
      MIT
    • A
      license
      B
      quality
      A
      maintenance
      Persistent memory MCP server that captures coding session context and automatically injects relevant memories into prompts using hybrid search for OpenCode and Claude Code.
      14
      73
      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

    TDQS

    A3.7/5.0

    Scored across 9 tools

    Disambiguation4/5

    The tools have mostly clear, distinct purposes: search vs. read, context retrieval vs. rule retrieval, and write vs. read. However, the context-retrieval tools (get_project_overview, get_task_context, get_domain_rules, get_related_decisions) overlap somewhat and rely on descriptions to tell them apart, and search_product_memory with full=True partially duplicates read_memory.

    Naming Consistency4/5

    Most tools follow a consistent get_/search_/read_/propose_ verb pattern, which makes the set predictable. why_code breaks the pattern as a noun-style tool name, and the mix of get_ with search_/read_ is a minor deviation.

    Tool Count5/5

    Nine tools is well within the ideal range for a product memory server, and each tool covers a distinct retrieval or write need. The count feels appropriately scoped without being bloated or thin.

    Completeness4/5

    The surface covers the core lifecycle well: search, read, targeted context retrieval, recent work, and recording new memories. There is no explicit update/delete/invalidation tool for memories, though the append-only/id-suffix design suggests this may be intentional; still, explicit correction would make it more complete.