原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

opendrs

作者:error-path版本 0.5.0i★ –i在你的电脑上运行
注册名称io.github.error-path/opendrs

安装

概览

作者提供的说明(英文原文)

PR blast radius and 0-1 risk score from git history, so low-risk PRs can be auto-approved.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 开发者工具

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "opendrs": {
      "command": "npx",
      "args": [
        "-y",
        "@error-path/opendrs",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add opendrs -- npx -y @error-path/opendrs mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "opendrs": {
      "command": "npx",
      "args": [
        "-y",
        "@error-path/opendrs",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "opendrs": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@error-path/opendrs",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 error-path 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“开发者工具”中的其他服务器比较i

  • 星标数多于此分类中其他 1383 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 1383 个服务器的 76% 更新
  • 基础检查结果等于或优于此分类中其他 1383 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

opendrs 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.5.0)于14天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:GitHub, Desktop Commander, Cloudflare MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

GitHub

作者:github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

电脑或云端★ 34,245MIT3天前更新
安装

Desktop Commander

作者:wonderwhy-er

MCP server for terminal commands, file operations, and process management

在你的电脑上运行★ 10,225MIT15天前更新
安装

Cloudflare MCP

作者:cloudflare

Cloudflare MCP servers

在云端运行★ 4,446Apache-2.014个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

opendrs: PR blast radius analyzer and risk score for safe auto-approval

A calibrated 0-1 risk score for every pull request, so AI-reviewed, low-blast-radius PRs can be auto-approved into the merge queue while risky ones still wait for a human.

AI agents now write and review code faster than people can read it, so human review has become the bottleneck. Most pull requests are low risk, and a few cause most incidents. opendrs measures each PR's blast radius and risk: what the change touches, how many files depend on it, the history of the files it changes, author experience, missing tests and critical paths. It turns that into a 0-1 score using signals from your own git history. A team then sets a policy. For example, a PR that scores below 0.3 and has passed an AI review (Claude, CodeRabbit, Copilot or any check run) is approved and sent to the merge queue or auto-merge. Riskier PRs still wait for a human. The approach follows Meta's Diff Risk Score (DRS); opendrs is an independent, open-source implementation that runs in any git repository, with no service to host.

Contents: Install · Quick start · How it works · Features · Results · CLI and MCP · Documentation · Limitations · Compared with other tools · Prior art

Install

Use it asCommandDetails
GitHub Actionuses: error-path/opendrs@v0 (Marketplace)Comments, labels and, optionally, approves and merges. GitHub Action reference
CLInpx @error-path/opendrs scoreCLI, MCP server, Claude Code plugin and agent skill
MCP server (any agent)npx -y @error-path/opendrs mcpTools: score_diff, explain_file_risk, list_hotspots, suggest_reviewers
Claude Code plugin (skill plus MCP server)/plugin marketplace add error-path/opendrs, then /plugin install opendrs@opendrs
Agent skill (Claude Code, Cursor, Codex and others)npx skills add error-path/opendrsskills/opendrs/SKILL.md
Docker (MCP server over stdio)docker build -t opendrs . && docker run -i --rm -v "$PWD:/repo" opendrsMount the repository to score at /repo

Website and guides: error-path.github.io/opendrs.

Quick start

Score your current branch against the default branch. No configuration or API key is needed:

npx @error-path/opendrs score

You get a score, a tier (green, yellow or red), the signals that drove it with their evidence, and the policy decision. --json prints the full result, and --fail-above 0.6 makes the command exit 1 above a threshold.

To score every pull request, add .github/workflows/opendrs.yml (or run npx @error-path/opendrs init):

name: opendrs

on: pull_request: types: [opened, synchronize, reopened, ready_for_review, labeled, unlabeled] permissions: contents: read pull-requests: write checks: read jobs: opendrs: runs-on: ubuntu-latest steps:

  • uses: actions/checkout@v5 with: fetch-depth: 0 # required: the score reads past commits and authors
  • uses: error-path/opendrs@v0

This only comments and labels. Approval is off until you turn it on in .opendrs.yml on your default branch; see how to auto-approve low-risk PRs and the GitHub Action reference.

How it works

flowchart LR

diff["git diff merge-base...head"] --> signals hist["git history"] --> signals imports["import graph"] --> signals llm["LLM judge (optional)"] --> signals signals["Signals each with evidence and provenance"] --> model["Logistic model score = sigmoid(b + Σ w·x)"] model --> tier["Tier green / yellow / red"] tier --> policy["Policy blocks, size cap, unknowns, AI review, sampling"] policy --> decision["auto-approve deferred-review waiting-ai-review human-review"]

  1. Signals. Each signal provider reads the diff, the history and the import graph and emits features: size, how spread out the change is, past fixes and reverts in the touched files, the author's experience with them, complexity, blast radius (transitive dependents), critical paths and missing tests. Every signal records how it was obtained (observed, derived, inferred or unknown) and the evidence behind it. All signals
  2. Model. A logistic regression turns the features into a probability. Each signal's contribution w·x is reported, so you can see why a PR scored what it did. Out of the box the weights are hand-set priors; opendrs calibrate fits them to your repository. Calibration and backtesting
  3. Tiers. The score maps to green, yellow or red, mirroring Meta's gates. Thresholds can be absolute scores or percentiles of your own history.
  4. Policy. Ordered rules turn the score into a decision. Policy and safety rails

Where opendrs sits in your PR flow

A PR now often gets two rounds of AI review before a human looks at it. Those rounds catch local defects: typos, missing null checks, an obvious off-by-one. By the time a human opens the PR, that work is done, and what is left is a design and architecture judgment call made with less context than before. opendrs is built for that moment: it tells the final human how much attention the PR needs and names up to five architecture and history facts — a new import between modules, a broken public contract, a file that usually changes with one the PR didn't touch — that neither the editor nor the AI review comments showed. See the captain brief.

Features

FeatureWhat it doesDefaultDocs
Risk signalsSize, spread, file history, author experience, complexity, blast radius, critical paths, tests, languageonSignals
Calibration and backtestFit the weights to your history and measure capture at 5 / 10 / 50 % gatedrun on demandCalibration
Hard blocks and safety railsBlocked paths, binaries, submodules, self-modification guard, sampling, stale-approval checksonPolicy
Auto-approvalApprove green PRs after your AI review passes, then auto-merge or the merge queueoffAuto-approve guide
LLM judgeClassifies every hunk into safe or risk categories; can only raise the scoreoffLLM judge
requireSafe gateAuto-approve only when the judge calls every hunk safe with enough confidenceoffLLM judge
Per-source policyHuman, bot or AI-agent PRs get their own stricter green, daily cap and track recordoffPolicy
Deferred reviewA PR just above green lands now and gets a post-merge reviewoffPolicy
Landing delayAn eligible PR waits before approval, so a human can vetooffPolicy
Freeze windowsSuspend or tighten auto-approval on weekends or peak datesoffPolicy
Content blocklistRegexes on added lines send a PR to a humanoffConfiguration
Reviewer assignmentOne of the top three experts is asked to review risky PRson in the ActionPolicy
HotspotsRank files by risk at restrun on demandCLI and MCP
Review briefRanks hunks to read first, fixed check questions, safe-to-skim list, hard-rule reasons — recipes for claude-code-action, Bugbot, CodeRabbit (limited), Copilot and Codex (paste)onLLM reviewers, CLI and MCP
Pre-PR self-checkLists the ids an author agent should fix or explain before opening the PR; opendrs reads the verdicts back from the head commit and adds one advisory line, never part of the gateoffSelf-check recipe
Verification passOne batched LLM call re-checks every captain fact, review-first hunk and check with fresh context and keeps, drops or downgrades each one; never changes the score, tier or policyoffVerification pass
Incident feedbackopendrs feedback records incidents for calibrationrun on demandCalibration

Every setting lives in .opendrs.yml, read from the base branch so a PR cannot loosen its own gate: configuration reference.

Results

BenchmarkResultDetails
ApacheJIT (15 Apache Java projects, official 2017–2019 test years, apache/hadoop left out because it has no positive labels)Calibrated opendrs: AUC 0.823; catches 67 % of buggy commits in its riskiest 30 %, on par with a regression on the classic JIT metrics (0.821, 66 %)Results on ApacheJIT
ApacheJIT with the LLM judge (Claude Sonnet 5, 800 sampled test commits)At confidence 8, the commits the judge calls all-safe are buggy at 5.3 %, against a 25.5 % base rateWith the structured LLM judge
27 public repositories (calibrate, then backtest)Calibration beat the default priors on held-out commits in all nine repositories of the first runBenchmark results

CLI and MCP

CommandWhat it does
opendrs scoreScore merge-base(base, head)..head
opendrs explain A file's history, fixes, authors, dependents and path policy
opendrs hotspotsRank files by risk at rest
opendrs calibrate / opendrs backtestFit the model to your history; compare default and calibrated models
opendrs feedbackRecord an incident in .opendrs/incidents.jsonl
opendrs initWrite a commented .opendrs.yml and a comment-only workflow
opendrs mcpRun the MCP server

Flags, exit codes, MCP tools and the agent skill: CLI, MCP server, Claude Code plugin and agent skill.

Documentation

PageRead it when you want to
Auto-approve low-risk PRsset up a risk-based approval gate step by step
GitHub Action referencelook up inputs, outputs, permissions, branch rules and the scheduled sweep
Policy and safety railsknow exactly why a PR was or was not approved
Configuration referencechange .opendrs.yml
Risk signalssee what opendrs measures and how
What is the blast radius of a PR?understand blast radius
LLM judgeturn on the optional LLM judge or the requireSafe gate
Feeding the review brief to an LLM reviewerget opendrs's findings in front of Claude Code, claude-code-action, Bugbot, CodeRabbit, Copilot or Codex
The captain briefknow what the final human reviewer sees: priority, reviewer, and the architecture and history facts
Verification passturn on an LLM re-check of the brief's facts before a human reads them

| [

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx