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Related Servers

Alternatives to agent-context

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      An MCP server that gives AI agents persistent, file-based memory stored as plain markdown files in a local git repository, enabling agents to remember, recall, and build on information across sessions.
      1 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      MCP server providing persistent, local-first memory for AI agents via Markdown files in a git repo, with search, branching, and auditability.
      3 npm
      2
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      An MCP server that gives AI coding agents persistent, cross-session memory by letting them save task insights as atomic markdown knowledge cards with bidirectional links and recall relevant cards before starting new work. Stores everything as plain markdown files that can be browsed, searched, and synced across clients and devices via git, with no vector database or embeddings required.
      4 npm
      ISC
    • A
      license
      A
      quality
      B
      maintenance
      A self-hosted MCP server that gives AI agents shared, long-term memory over a git-backed folder of markdown, enabling persistent knowledge search, read, and write without a database.
      16
      6 npm
      17
      MIT

    TDQS

    A4.3/5.0

    Scored across 5 tools

    Disambiguation4/5

    Each tool targets a distinct action: reading full context, listing files, recording a note, recording a decision, and updating a plan. The only potential overlap is between get_context and list_context, but their descriptions clearly differentiate content retrieval from file listing.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (get_context, record_note, record_decision, update_plan, list_context) using snake_case. The verbs are descriptive and the pattern is uniform across the set.

    Tool Count5/5

    With 5 tools, the server is well-scoped for managing AI context. Each tool serves a clear purpose without redundancy, and the count is appropriate for the narrow domain.

    Completeness4/5

    The set covers the core workflow: reading the full context, listing stored files, and writing notes, decisions, and plans. Minor gaps exist (e.g., no direct note or decision deletion/editing), but these are acceptable given the 'permanent' nature of decisions and the mutable plan overwrite capability.

    Maintenance

    ActivityStale
    ResponsivenessNo issues