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Related Servers

Alternatives to lore-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Automatically extracts architectural decisions, patterns, and insights from Git commits to build a local, structured project memory. It exposes this living context to AI tools via MCP, allowing them to understand the historical reasoning and evolution behind your codebase.
      19 npm
      6
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides persistent memory for AI coding assistants, storing and retrieving architectural decisions, patterns, and solutions across sessions using semantic search, while also offering git integration for commit messages and code expertise mapping.
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides AI coding assistants with persistent, context-rich memory of a codebase, including documentation and git history, enabling recall across sessions.
      105
      Apache 2.0
    • 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
      173 PyPI
      850
      MIT

    TDQS

    A3.7/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: get_context retrieves existing decisions, get_gaps identifies implementation issues, and record_decision logs new choices. There is no overlap in functionality, making tool selection straightforward for an agent.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern (get_context, get_gaps, record_decision) with clear, descriptive names. The naming style is uniform and predictable throughout the set.

    Tool Count4/5

    Three tools are appropriate for the server's purpose of managing architectural decisions, covering retrieval, gap analysis, and recording. While slightly minimal, each tool serves a distinct and necessary function without redundancy.

    Completeness4/5

    The tool set covers the core lifecycle of architectural decisions: retrieving context, identifying gaps, and recording new decisions. A minor gap exists in updating or deleting decisions, but agents can likely work around this for basic workflows.

    Maintenance

    ActivityInactive
    ResponsivenessSyncing