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612,594 tools. Updated 2026-09-26 17:03

"Automating Testing and Debugging for LLMs in Production" matching MCP tools:

  • Get a snapshot of every release track—internal, closed testing, open testing, production—showing version codes, rollout status, and staged-rollout percentages to pinpoint exactly where your release stands.
    MIT
  • Switch Hedera blockchain networks to configure SDK connections, mirror nodes, and RPC endpoints for development, testing, or production deployment.
    Apache 2.0
  • Start a background Grok job for implementation, debugging, testing, or review. It can edit files and run commands in the working directory; poll the returned job ID for completion.
    MIT
    Destructive
  • Create a custom closed-testing track for your app. Set up additional named tracks beyond internal, alpha, beta, and production to manage testing groups.
    Apache 2.0

Matching MCP Servers

  • F
    license
    A
    quality
    D
    maintenance
    Enables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.
    9
    -
  • A
    license
    Not graded
    quality
    D
    maintenance
    An MCP server that exposes the llms.txt file and its referenced local or external resources from a project root to provide context for AI models. It automatically parses documentation links and URLs to make them accessible as additional MCP resources.
    1
    MIT

Matching MCP Connectors

  • Create and run a Kubernetes pod with a specified container image for one-off tasks, debugging, or testing. Supports custom commands, environment variables, and restart policy.
    Apache 2.0
  • Decode JWT tokens to inspect header and payload, check expiry status, or create unsigned tokens for testing. Not for production authentication.
    MIT
  • Retrieve a list of Marcus Oates's projects, with optional filtering by status: production, testing, or proof of concept.
    -
  • Monitor and verify AI orchestration system health, model configurations, and capability test outcomes to ensure system readiness and aid in debugging processes.
    -
  • Generate production-ready RAG architecture blueprints with vector DBs (ChromaDB, Qdrant, Pinecone), local LLMs (Ollama, vLLM), and LangGraph/LangChain orchestration for any target use case.
    MIT
  • Run a specific agent-readiness check (e.g., a2a-agent-card, llms-txt) on a URL to validate a fix or debug a signal. Get status, evidence, and actionable fix recommendations.
    MIT
  • Enable or disable server-side caching for a website to speed up page loads and reduce server load. Use it to improve production site performance or turn caching off when debugging requires live content.
    MIT
    Destructive