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Related Servers

Alternatives to super-loop-mcp

No user-submitted related servers found.

    Related Servers

    • A
      license
      C
      quality
      C
      maintenance
      A referee for self-improving AI agent loops that mines past sessions for effective workflows, improves them, and requires measured proof before declaring anything better or done, never stopping until the user stops it.
      29
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI coding agents to retrieve relevant execution context before a task, compare candidate paths, log outcomes, and search past experiences stored locally in SQLite. It lets agents reuse what worked on similar tasks and get live alerts when a run stagnates or repeats failures.
      4
      14
      200 PyPI
      3
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables creative software agents to operate within bounded, temporary workcells, handling scored objectives through autonomous inspect, execute, capture, and correct loops while producing evidence-backed receipts for human review.
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables personal AI agents to perceive ambient context, retain episodic memory with decay, act proactively, and route routine decisions through fast System-1 reflexes while escalating ambiguous multi-hop plans to frontier LLMs. Includes reversible execution checkpoints, token budgets, and local-first memory retention, and plugs into MCP clients like Claude Desktop, Cursor, and Windsurf.
      7
      MIT

    TDQS

    B3.1/5.0

    Scored across 25 tools

    Disambiguation4/5

    Tools are largely distinct, each serving a specific phase (e.g., benchmarking, hypothesis testing, campaign status). The only minor issue is 'loop_next' being an alias for 'request_next_phase', but this does not cause significant confusion.

    Naming Consistency3/5

    Naming patterns are mixed: some follow verb_noun (e.g., 'initialize_loop_run', 'register_hypotheses'), while others use noun_verb (e.g., 'loop_start', 'benchmark_propose') or compound nouns (e.g., 'promotion_request', 'campaign_status'). This inconsistency can make it harder for an agent to predict tool names.

    Tool Count3/5

    With 25 tools, the server is at the high end for a single MCP. While each tool serves a distinct role in the complex loop-based workflow, the count feels slightly heavy and could be streamlined by combining some related operations.

    Completeness4/5

    The tool set covers the entire campaign lifecycle: initialization, phase-gated loops, evidence recording, benchmarking, hypothesis testing, promotion, status, review, and export. Minor gaps exist (e.g., no tool to update or delete registered loops), but the core workflow is well-supported.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues