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OpenWorkProof

by dengyierversion 1.6.1i★ –iRuns on your computer
Registry nameio.github.dengyier/OpenWorkProof

Install

Overview

Description from the maker (original English)

Verifiable agent evidence; opt-in Codex guard and reference SOC alert review.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "openworkproof": {
      "command": "uvx",
      "args": [
        "openworkproof"
      ]
    }
  }
}

Run this in your terminal

claude mcp add openworkproof -- uvx openworkproof

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "openworkproof": {
      "command": "uvx",
      "args": [
        "openworkproof"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "openworkproof": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "openworkproof"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account dengyier, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32435 servers in this category
  • Published to the registry more recently than 89% of the other 32435 servers in this category
  • Basic checks equal to or better than 100% of the other 32435 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is OpenWorkProof safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.6.1) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Apify MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Spec Driven Development

by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
Install

Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
Install

Extract data from any website with thousands of scrapers, crawlers, and automations on Apify Store ⚡

Runs in the cloudUpdated today
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

OpenWorkProof

English · 简体中文

Check what an AI agent was allowed to do, what it recorded, and whether its evidence holds up.

OpenWorkProof (OWP) is an open-source toolkit for developers and teams using AI agents. Use it to review signed work records, check exported evidence, or run a bounded Codex preview-editing task. Security engineers can also try a reference workflow for reviewing Slips alerts.

You keep the final decision to accept or reject the result. Connecting OWP to an agent gives it tools; protection of a Codex task requires a separate Guard setup.

Get started · Codex Guard · Docs · Community

Current release: 1.6.1 · PyPI · Release notes · MCP Registry

What can you do with it?

Your taskWhat OWP helps you doStart here
Review an agent's work recordsCheck signed task scope, recorded actions and evidence; export a bundle another reviewer can inspect. Your integration must supply the records.MCP tools, offline verification
Let Codex edit a preview copyExplicitly allow supported text edits inside one preview directory and reject out-of-scope requests in the guarded launch path.Guard setup — experimental
Review Slips alert dataGroup supplied JSONL alerts into review cases, inspect simulated decisions and export a signed evidence bundle.SOC walkthrough — reference implementation
Add evidence review to a delivery workflowIntegrate verification into a GitHub Action or your own agent workflow, then keep human acceptance as a separate step.GitHub Action example, integration details

OWP does not automatically watch every agent or tool on your computer. Fleet permissions, WorkBuddy integration and live SOC remediation are not part of the verified release paths above.

Get started with MCP

You need Python 3.10+, uv, and an MCP-capable client. Add this local stdio server to the client's MCP configuration:

{

"mcpServers": { "openworkproof": { "command": "uvx", "args": ["openworkproof==1.6.1"] } } }

This is the common mcpServers configuration shape. Some clients use a different file or top-level key; see the client-specific setup. uvx downloads the package and dependencies when needed. OWP does not require an OWP cloud account or API key.

After the client connects, it should discover 32 tools. Try this first with the included synthetic data:

Use owp_soc_sample_alerts to get the OpenWorkProof sample. Pass its alerts_jsonl to owp_soc_analyze_slips, then pass the returned bundle to owp_soc_verify_bundle. Explain the cases and simulated actions. Do not operate a real host. If independently obtained trusted keys and checkpoints are missing, keep the verification result UNKNOWN and explain what is missing.

You should receive a case summary and evidence bundle. `UNKNOWN` is expected without independent trust information; it does not mean installation failed. This sample uses a deterministic investigation stub and simulated actions. It does not test detection accuracy or remediate a host.

To use your own alerts, follow the SOC guide. Alert content is returned to your MCP client and can enter its model conversation, so use data you are authorized to share with that client.

Optional: install the SOC Review Skill

The Skill gives your agent a repeatable procedure for using those tools. With Node.js/npm available:

npx skills add dengyier/OpenWorkProof --skill openworkproof-soc-review

Choose your agent and install scope in the installer. Read the instructions first, or use the release ZIP.

The Skill does not configure MCP or enable Guard. Configure the MCP server above separately. Your client's usual model charges still apply.

Try Codex preview protection

Experimental, separately enabled. Guard is for supported local text-editing tasks in a designated preview directory. Use a new test project or a copy you own first.

Read the English first-run guide before enabling. It includes a complete test project, scope review, expected checks and uninstall steps. The approval prompts are currently in Chinese, while the default output is JSON. Review the scope yourself and enter yes only when you understand it; do not use a trust shortcut to skip that review.

enable runs a live probe and run uses your existing Codex login and model allowance. Continue only after doctor confirms the required setup, current review and live probe. Ordinary Codex launches are not automatically protected.

The recorded live-host baseline covers macOS, Python 3.12 and Codex CLI 0.147.0, from the Guard implementation introduced in 1.5.0. Check compatibility and rerun the probe in your own environment. Builds, deployment, online search, personal MCP/plugins and whole-computer isolation are outside this launch path. See scope and limitations.

Install the CLI package, then run these commands from your target Git project after creating a preview directory and a text file such as preview/index.html:

uv tool install --python 3.12 'openworkproof==1.6.1'

owp-guard install --project "$(pwd -P)" --allow-dir preview owp-guard enable --project "$(pwd -P)" owp-guard doctor --project "$(pwd -P)" owp-guard run --project "$(pwd -P)" --prompt "Update the heading in preview/index.html. Keep the change in preview; do not publish."

Check an evidence bundle from the command line

Already have an OWP bundle? Install the package as above, then use the command matching its format:

# Core Surface Bundle

owp surface-verify /path/to/surface-bundle

Core Acceptance Bundle

owp acceptance-bundle-verify /path/to/acceptance-bundle

SOC reference output; missing external trust intentionally returns UNKNOWN/nonzero

owp-aisoc verify /path/to/soc-review

These formats and their trust requirements differ. Follow the Core verification guide or SOC trust guide. Obtain expected public keys and checkpoints through a separate trusted route; copying them from an untrusted bundle does not establish who you are trusting.

What a result means

  • Verification checks evidence under the stated scope and trust inputs. It does not establish that a business outcome is correct. Core VERIFIED and binding BOUND do not mean customer acceptance or payment.
  • Human acceptance is separate. The intended reviewer keeps the decision to accept or reject a delivery. See the acceptance workflow.
  • SOC results are reference results. Investigation is a deterministic stub; actions and acceptance statuses are simulated. There is no live SOC deployment, production detection benchmark, OS isolation or HSM in this integration.
  • Signing tools can handle sensitive keys. Generic key-generation/signing tools can return or accept private-key material. Keep production signing keys out of model conversations and use an externally controlled signing workflow.

OWP is open source. The current package and Skill are free to use under their licenses; your model provider and infrastructure may charge separately. Public listings, automated scores and engineering tests are not customer adoption or a security certification.

Documentation

NeedDocumentation
Connect MCP and understand the 32 toolsMCP setup and tool reference
Review Slips alerts and install the SkillSOC walkthrough
Set up a guarded Codex taskEnglish guide · 中文指南
Build an integration with signed task scope and human authorityHuman Agency protocol · runnable example
Understand protocol mechanics and historical validationEnglish reference · 中文参考 · status
Report a reproducible problem or contributeContributing · Issues

Community and contributing

The card is a live directory badge; follow it for the scanned version and scope. Find OWP on MCPRush, Glama, and AgentSkills.in.

The community record preserves directory contributions, external research, integration experiments and technical writing, with their original links and checked dates. These records have different scopes and do not imply endorsement or production adoption.

Contribute a reproducible bug report, an integration, or a documentation improvement. Please report security issues privately through GitHub Security Advisories.

License

OWP Core: Apache-2.0. Tim / alphatin123's contributed aisoc component: MIT. The combined package metadata uses `Apache-2.0 AND M

Only the beginning is shown; read the rest in the repo

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