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DevPilot MCP

PyPI Tests License: MIT

Chat with a code repository and watch exactly what the AI does. DevPilot lets an AI model read, search and inspect one repository through 18 safe tools, and it never changes a file or runs tests without your approval.

It has two parts:

  • DevPilot Studio: a local web UI. This is the easiest way to use it (see below).
  • DevPilot MCP server: the same 18 tools for any MCP client, such as Claude Code or Gemini.

DevPilot Studio: asking a question, watching the steps, a blocked secret file, and an approved change that is then undone

Watch the full 85-second demo (MP4)

Requires Python 3.10+ (3.11+ recommended). Git is needed for the Git tools.

pip install "devpilot-mcp[ui]"
$env:DEVPILOT_WORKSPACE = "C:\path\to\your\repo"     # macOS/Linux: export DEVPILOT_WORKSPACE=/path/to/your/repo
devpilot-ui

Your browser opens at http://127.0.0.1:8765. Then:

  1. Try it right away, no account needed. Click a quick action (Analyze, Git status, Commits), press Ctrl+K to run any tool, or open the Files tab to browse the code.
  2. Turn on AI chat (optional). Get a free token at aipipe.org/login, then set it and restart:
    $env:AIPIPE_TOKEN = "your-token"     # macOS/Linux: export AIPIPE_TOKEN=your-token
    devpilot-ui
    
  3. Ask a question, like "Where is authentication implemented?" Each answer shows the steps the AI took.

Without a token, everything works except the chat. The full guide is in the Web UI docs.

What DevPilot Studio gives you

  • Steps you can follow: every answer lists the tools the AI used, with timings. Anything DevPilot's security refuses (for example reading .env) is shown as blocked.
  • Result cards, not JSON: language bars, commit timelines, colored diffs, grouped search matches, test results.
  • Ctrl+K tool runner: run any of the 18 tools through a form, no AI needed.
  • File explorer: browse the repository, open files, and ask the AI about one.
  • Changes with Undo: every patch the AI applied is listed with its diff and a one-click undo.
  • Approval first: changes and test runs always wait for you to click Approve.
Steps you can follow Result cards, secrets blocked Approval with the exact diff
A list of the tool calls the AI made for one answer An analysis card and a blocked read of the .env file The approval dialog showing a colored diff

Use DevPilot from an AI client (MCP)

The same tools work in any app that supports MCP over stdio. With Claude Code, for example:

pip install devpilot-mcp
claude mcp add devpilot -e DEVPILOT_WORKSPACE=C:/path/to/your/repo -- devpilot-mcp

Then ask: "Use DevPilot to analyze this repository and explain its structure." You can also explore the tools by hand with MCP Inspector (npx @modelcontextprotocol/inspector). More in the usage guide.

Always set DEVPILOT_WORKSPACE to the absolute path of the repository. If devpilot-mcp is not on your PATH (for example it is inside a virtual environment), give claude mcp add the full path to the devpilot-mcp executable instead.

The 18 tools

Tool What it does Access
list_directory List a directory Read-only
read_file Read a text file Read-only
search_files Search text in all files, optionally in one folder Read-only
search_code Smart-case search in source files Read-only
analyze_repository Languages, structure, manifests, tests, entry points Read-only
git_status Branch, staged, unstaged and untracked files Read-only
git_log Recent commits Read-only
git_diff Staged or unstaged changes Read-only
git_branch Local branches Read-only
github_repository GitHub metadata for origin Read-only
github_issues Recent issues Read-only
github_pull_requests Recent pull requests Read-only
investigate_repository Ranked evidence for a developer question Read-only
apply_patch Apply a unified diff you supply, atomically Writes files
revert_patch Undo an applied patch Writes files
get_test_commands Detect pytest/unittest (runs nothing) Read-only
run_tests Run the detected test command Executes code
validate_repository Validation report; tests only on request Executes code

DevPilot collects evidence and performs tightly bounded actions. The AI model does the reasoning, and it never writes a patch on DevPilot's behalf: patches come from the model or from you.

Security at a glance

  • Every path stays inside the workspace. .., absolute, drive and UNC paths, and escaping symlinks and junctions are rejected.
  • .env files, private keys, credential files and .git internals are never read, searched or written.
  • Changes and test runs need your explicit approval in the UI, and patches are validated in full and applied atomically.
  • Only two places start processes: allowlisted read-only Git commands, and two fixed Python test commands. There is no shell and no caller-supplied command.
  • GitHub access is HTTPS GET to api.github.com only, and the token never appears in output.
  • The UI listens on 127.0.0.1 only, and your AI token stays on the server side.

It is not a sandbox. Tests run with DevPilot's own permissions and network access, and secret redaction is best-effort. See Security for the full model and known limitations.

Run from source

git clone https://github.com/KD-kaustubh/devpilot-mcp.git
cd devpilot-mcp
python -m venv .venv
.venv\Scripts\activate           # macOS/Linux: source .venv/bin/activate
pip install -e ".[ui]"
python -m unittest discover -s tests -t .

The UI frontend needs Node.js to rebuild (cd ui && npm install && npm run build); see Development.

Documentation

Document Contents
Web UI DevPilot Studio: setup, AI Pipe, approvals, safety, development
Usage guide Configuration, MCP Inspector, client setup, example workflows
Tool reference Every tool's inputs, output examples and limits
Security Security model, known limitations, security tests
Development Architecture, running tests, CI, phase history

License

MIT

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