About deltaprobe
deltaprobe is an MCP server for developers and AI assistants reviewing GitHub pull requests. It provides PR listings, diffs, summaries, rule-based risk checks, and inline review comments, with comment lines validated against the diff.
Key features
- 01List recently updated open pull requests
- 02Summarize PR scope, status, and CI results
- 03Retrieve diffs within a character budget
- 04Run rule-based patch risk checks
- 05Post inline reviews with dry-run preview
Use cases
- 01Survey open pull requests in a repository
- 02Understand a PR before reviewing its changes
- 03Flag risky changes such as secrets or missing tests
- 04Post inline feedback on changed lines
MCP support
Exposes GitHub pull-request tools to MCP clients over stdio. It fetches and trims GitHub data; the assistant selects tools and composes the review.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y deltaprobeGITHUB_TOKENSecretGitHub token. Optional for reading public repos; needs 'Pull requests: Read and write' to post reviews.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEdeltaprobe 🔍
Give your AI assistant x-ray vision into pull requests.
deltaprobe is a Model Context Protocol (MCP) server that lets AI assistants like Claude, Cursor and VS Code Copilot probe GitHub pull requests: list them, read their diffs, summarize changes, flag risky patches and post review comments.
Available on npm and the official MCP Registry as io.github.Deepthi-04/deltaprobe.
Tools
| Tool | Status | Description |
|---|---|---|
list_open_prs | ✅ | List open PRs in a repo, most recently updated first |
summarize_pr | ✅ | Overview of a PR: description, size, file types, most-touched areas, review status and CI results |
get_pr_diff | ✅ | Fetch changed files and diff hunks, trimmed to whole hunks within a character budget |
check_pr_risk | ✅ | Rule-based risk checks: secrets in added lines (masked), sensitive files, large diffs, missing tests, CI/migration/dependency changes, debug code |
post_review_comment | ✅ | Post a review with inline comments; every line is checked against the diff first, with a dryRun preview |
How it works
You: "Review PR #42 in acme/app"
│
▼
AI assistant ──(MCP over stdio)──► deltaprobe ──► GitHub API
▲ │
└──── structured PR data ◄──────┘
The assistant decides which deltaprobe tools to call, deltaprobe fetches and trims the data from GitHub, and the assistant writes the review.
Quick start
Prerequisites
- Node.js 20+ (22.12+ for development)
- A GitHub token (create one). Optional for reading public repos, but it raises the rate limit from 60 to 5,000 requests/hour.
post_review_commentneeds one with Pull requests: Read and write permission.
Use with Claude Code
# public repos, read-only (no token)
claude mcp add deltaprobe -- npx -y deltaprobe
# with a token (higher rate limit, private repos, posting reviews)
claude mcp add deltaprobe -e GITHUB_TOKEN=<your-token> -- npx -y deltaprobe
Use with Claude Desktop / Cursor
Add to your MCP config:
{
"mcpServers": {
"deltaprobe": {
"command": "npx",
"args": ["-y", "deltaprobe"],
"env": { "GITHUB_TOKEN": "<your-token>" }
}
}
}
Then ask: "What are the open PRs in modelcontextprotocol/typescript-sdk?"
Development
git clone https://github.com/Deepthi-04/deltaprobe.git
cd deltaprobe
npm install
npm test # run unit tests
npm run build # compile TypeScript to dist/
npm run dev # run the server from source
Project structure
src/
├── index.ts # MCP server entry: registers tools, connects over stdio
├── github.ts # GitHub API client
├── diff.ts # hunk splitting, budget fitting, commentable lines
├── files.ts # file type and area classification
├── risk/rules.ts # risk rules: each takes the PR's files and returns findings
└── tools/ # one file per tool
test/ # vitest unit tests
Roadmap
-
list_open_prs -
get_pr_diffwith smart truncation -
summarize_pr -
check_pr_riskrules -
post_review_comment - CI on GitHub Actions
- Publish to npm and the MCP Registry
- List on Smithery
- GitHub Action that reviews PRs automatically
License
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.