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Related Servers

Alternatives to PCQ

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to track ML experiments with a reproducible write contract, internal git snapshots, and a queryable knowledge graph, plus a live web UI for humans.
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables provider-neutral policy enforcement, identity, persistent storage, and telemetry collection for reinforcement learning, evaluation, analytics, replay, and downstream dataset generation across standalone applications and agent systems.
      0
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables LLM agents to drive a data-poisoning detection research pipeline through 28 typed tools: generate poisoned datasets with published attacks, configure and launch detection experiments, follow logs, compare runs, inspect flagged samples, and export sanitized datasets.
      24
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      A scientific experiment log MCP server for AI agents that stores predictions, causal claims, and verdicts, enabling queryable causal maps and calibration of intuition over diagnostics.
      17
      MIT
    • A
      license
      B
      quality
      A
      maintenance
      Enables AI tools and agents to form contract-bound organizations, execute persistent task DAGs with independent audits, score decisions with counterfactual trees, run time-compressed world simulations, and control an on-demand localhost dashboard via stdio tools.
      6
      1
      Apache 2.0
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents and their users to submit, route, and monitor training jobs across free-tier GPU clouds (Kaggle, Colab, Lightning, local MPS) through a local daemon that tracks quota, explains routing decisions, and gates long or secret-reading agent jobs behind human approval.
      8
      MIT

    TDQS

    A3.7/5.0

    Scored across 14 tools

    Disambiguation5/5

    Each tool targets a distinct phase or action: plan application, scaffolding, execution, finalization/validation, and run analysis. The read-only analysis tools (describe_run, compare_runs, lineage_chain) and project inspection tools (resolve_project, inspect_project, validate_project) are separated by clear semantic boundaries. There are no pairs that appear to do the same thing.

    Naming Consistency4/5

    Most tools follow an imperative verb_noun pattern (run_experiment, validate_project, describe_run). A few deviate: agent_install and agent_status are noun-first, lineage_chain is a noun phrase, and apply_planset compresses plan_set into one word. These are minor and do not prevent readability.

    Tool Count5/5

    At 14 tools, the surface is within the well-scoped range and each tool covers a discrete step in the CQ lifecycle. The grouping of scaffold/configure/run/finalize/validate/analyze plus agent asset helpers feels intentional, with no obvious dead weight.

    Completeness4/5

    The main lifecycle is well covered: init, plan application, run, finalize, validate, and analyze. Minor gaps exist around explicit discovery/cleanup (e.g., listing or removing plans/runs), but agents can work around these using inspect_project, finalize_run artifacts, or output directories.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues