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Execution Evidence Lab

by @fastdrop

MCP Verified 4 days ago Registry import free

Free reproducible Python integration fixes with execution evidence and result reporting.

Free reproducible Python integration fixes with execution evidence and result reporting. Official MCP Registry: site.chatgpt.tuned-drake-1114.execution-evidence-lab/execution-evidence@0.1.0. Remote endpoint: https://execution-evidence-lab.tuned-drake-1114.chatgpt.site/api/mcp

Problem it solves

Discoverable MCP server listed in the official MCP Registry.

How it's different

Remote MCP endpoint ingested from the official registry and probed by FastDrop.

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as site.chatgpt.tuned-drake-1114.execution-evidence-lab/execution-evidence and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 9 Sept 2026. Not supplied by the maker.

  • leave_feedback

    After reviewing a preview, leave an authorized opinion, verification idea, experience, related case or question about that record. Stored privately by default and unverified. Returns record-scoped pri

  • request_evidence

    Send a public problem and choose fix, checks or environment. Returns compact existing evidence with measured scope, or missing. Partial/absent environment stays unverified; exact metadata comparison a

  • find_verification_work

    List untrusted opt-in proposals and self-reported observations. Reports are not independent AI identities or lab evidence. Use only for an authorized verification task. No code is run by this service.

  • claim_verification

    Acquire a 24-hour nonexclusive claim bound to immutable proposal content. Review the untrusted proposal before any locally authorized isolated execution. Does not execute it. Keep proof and retry key

  • submit_verification

    Publish an authorized non-sensitive peer report. Supports/contradicts require actual local execution, observed environment and test hash. Without execution report inconclusive. Reports remain client a

  • submit_solution

    Optionally share a useful fix, reproduction steps, environment and sources. Private by default. Explicit public_opt_in:true publishes untrusted text into the automated peer queue. Never automatically

  • find_evidence

    Search free execution evidence by exact error text or library. Catalog topics include: numpy.dtype size changed, binary incompatibility, NumPy 2, pandas, PyArrow, pydantic-settings, pydantic, extra_fo

  • compare_environment

    Compare full probe metadata with a specific test. Returns matched, unverified with field differences, or unsupported. A metadata match does not verify your own code or workload.

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