google-jules-mcp-server

If you're searching for a way to drive Google's Jules coding agent from Claude, Cursor, VS Code Copilot, or any other MCP client, this is that bridge. google-jules-mcp-server is an unofficial Model Context Protocol server that exposes the full Jules API (v1alpha) as 13 tools, so your assistant can create sessions, poll status, approve plans, and fetch the resulting pull request without you leaving the chat.

Developers running Jules across many repositories at once use it to let their AI assistant manage the whole async workflow: kick off a task, check on it later, and hand back a PR link when it's done, instead of switching to the Jules web app to babysit progress. Every response is validated at runtime through Zod schemas, so a drifted Jules API response fails loudly rather than silently breaking downstream code.

Model Context Protocol (MCP) server for Google's Jules AI coding agent — unofficial. Lets AI assistants like Claude create and manage asynchronous coding tasks through the Jules API v1alpha.

Overview

Jules is Google's AI coding agent that executes development tasks in isolated cloud VMs — generating code, fixing bugs, writing tests, updating dependencies, and refactoring across files. This server exposes the full Jules API surface as 13 MCP tools, covering repository sources, session lifecycle, and activity logs.

Tasks run asynchronously and typically complete in 5–60 minutes depending on complexity.

Related MCP server: Jules API MCP

Architecture

The server is organized by Jules resource domain rather than as one flat file:

src/
├── index.ts                 # entrypoint: connects the stdio transport
├── server.ts                 # createServer(): wires the MCP server + all tool registrations
├── core/                     # transport-agnostic: auth, HTTP client, retry/backoff, typed errors, logging
└── resources/
    ├── sources/               # jules_list_sources, jules_get_source
    ├── sessions/              # session lifecycle (create/list/status/message/approve/output/delete/archive/unarchive)
    └── activities/            # jules_list_activities, jules_get_activity

Each resource module owns its own Zod schemas, a typed API client, and its MCP tool registrations. Zod schemas are the single source of truth: TypeScript types are inferred from them (z.infer), and every Jules API response is validated at runtime through core/http-client.ts — so a drifted API response fails loudly as a JulesResponseValidationError instead of silently producing undefineds downstream.

core/http-client.ts also centralizes retry-with-backoff (bounded, honors Retry-After) and a typed error hierarchy (JulesAuthError, JulesNotFoundError, JulesRateLimitError, JulesServerError, JulesClientError, JulesNetworkError, JulesResponseValidationError) so callers can distinguish failure modes programmatically rather than pattern-matching error strings.

Prerequisites

1. Google Account with Jules access

2. Jules API Key — get one from https://jules.google.com/settings#api (up to 3 keys allowed)

3. GitHub Integration — install the Jules GitHub app at https://jules.google.com to connect repositories

4. Node.js 22+

Quick Start

1. Install

The package is published on npm as google-jules-mcp-server. Most MCP clients can run it directly via npx — no separate install step needed, skip to step 2.

If you'd rather install it once instead of letting your client invoke npx on every launch:

npm install -g google-jules-mcp-server

This puts a google-jules-mcp binary on your PATH.

Building from source (for contributors, or to run unreleased changes):

git clone https://github.com/georgeracu/google-jules-mcp-server.git
cd google-jules-mcp-server
npm install
npm run build

2. Configure your API key

Get a key from https://jules.google.com/settings#api. Set it directly in your MCP client's server config (see below) — that's the only place it needs to live for normal use.

If you're building from source and want to run npm run test:smoke or use .env for local scripts:

cp .env.example .env
# edit .env and set JULES_API_KEY

3. Register the server with your MCP client

Claude Desktop — edit the config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "jules": {
      "command": "npx",
      "args": ["-y", "google-jules-mcp-server"],
      "env": { "JULES_API_KEY": "your_actual_jules_api_key_here" }
    }
  }
}

Claude Code:

claude mcp add jules -s user -e JULES_API_KEY=your_actual_jules_api_key_here -- npx -y google-jules-mcp-server

GitHub Copilot CLI:

copilot mcp add jules -e JULES_API_KEY=your_actual_jules_api_key_here -- npx -y google-jules-mcp-server

Or edit ~/.copilot/mcp-config.json directly:

{
  "mcpServers": {
    "jules": {
      "type": "local",
      "command": "npx",
      "args": ["-y", "google-jules-mcp-server"],
      "env": { "JULES_API_KEY": "your_actual_jules_api_key_here" },
      "tools": ["*"]
    }
  }
}

VS Code (Copilot Chat agent mode) — via terminal:

code --add-mcp '{"name":"jules","command":"npx","args":["-y","google-jules-mcp-server"],"env":{"JULES_API_KEY":"your_actual_jules_api_key_here"}}'

Or add to .vscode/mcp.json (workspace) or via MCP: Open User Configuration (user-level):

{
  "servers": {
    "jules": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "google-jules-mcp-server"],
      "env": { "JULES_API_KEY": "your_actual_jules_api_key_here" }
    }
  }
}

Cursor — add to ~/.cursor/mcp.json (global) or .cursor/mcp.json (project-only):

{
  "mcpServers": {
    "jules": {
      "command": "npx",
      "args": ["-y", "google-jules-mcp-server"],
      "env": { "JULES_API_KEY": "your_actual_jules_api_key_here" }
    }
  }
}

OpenAI Codex CLI:

codex mcp add jules --env JULES_API_KEY=your_actual_jules_api_key_here -- npx -y google-jules-mcp-server

Or edit ~/.codex/config.toml directly:

[mcp_servers.jules]
command = "npx"
args = ["-y", "google-jules-mcp-server"]
env = { JULES_API_KEY = "your_actual_jules_api_key_here" }

If you installed globally instead, replace "command": "npx", "args": ["-y", "google-jules-mcp-server"] with "command": "google-jules-mcp", "args": [] (and any npx -y google-jules-mcp-server in a CLI command above with just google-jules-mcp).

If you're running from a local clone instead, use "command": "node", "args": ["/absolute/path/to/google-jules-mcp-server/build/index.js"] (an absolute path to build/index.js).

Behind a corporate proxy — to support enterprise/corporate proxy setups without requiring any server-side config, the server automatically picks up proxy settings from the environment. The underlying EnvHttpProxyAgent (from undici) honours the standard HTTPS_PROXY, https_proxy, HTTP_PROXY, http_proxy, and NO_PROXY variables. What catches people out is that your MCP client spawns the server as a child process, so a variable exported in ~/.zshrc never reaches a GUI-launched app. Set it in the same env block as your API key:

{
  "mcpServers": {
    "jules": {
      "command": "npx",
      "args": ["-y", "google-jules-mcp-server"],
      "env": {
        "JULES_API_KEY": "your_actual_jules_api_key_here",
        "HTTPS_PROXY": "http://proxy.example.com:8080",
        "NO_PROXY": "localhost,127.0.0.1"
      }
    }
  }
}

Proxied requests are broken in 0.2.3 and earlier, where every call fails on a gzipped response the client never decoded. If you hit that, upgrade rather than reconfigure.

Restart your client after editing its config.

4. Verify

Ask your assistant: "List my Jules repositories." You should see the jules server connected with 16 tools available.

Available Tools

Output Size and Pagination

Everything these tools return lands in your assistant's context window, and an autonomous coding session can produce very long agent messages, progress descriptions and plans of hundreds of steps. The server therefore caps what it hands back, and says so in-band whenever it cuts something, so the assistant can decide whether to go and fetch the rest.

A capped entry in jules_list_activities names the sessionId and activityId needed to re-request it through jules_get_activity, which renders the same activity under the much larger single-activity budget — ten times the room, though not unlimited. The 8,000-character cap is the end of the line: there is no continuation token or offset for a single activity, so a jules_get_activity response that reports omitted characters says so explicitly rather than pointing anywhere else. Re-requesting it returns the same truncation.

If whole entries had to be dropped to stay inside the page budget, the response ends with Showing 12 of 40 activities; the fix there is a smaller limit, not the page token, since the token resumes after the entire requested page and would skip the entries you didn't see.

Pagination itself is unaffected by any of this. jules_list_sources, jules_list_sessions and jules_list_activities all accept pageSize (or limit) and pageToken, and echo the API's nextPageToken back when more results exist.

Async Workflow Pattern

1. Create a session — returns immediately with a session ID.

2. Poll every 10–30 seconds with jules_get_status.

3. Monitor detailed progress with jules_list_activities.

4. Retrieve the pull request URL once state is COMPLETED, via jules_get_session_output.

Your assistant handles this polling loop automatically when asked to monitor a task.

Session Watcher (Stuck Sessions)

If you don't want your LLM client burning tokens polling for stuck sessions (e.g. AWAITING_PLAN_APPROVAL or AWAITING_USER_FEEDBACK), you can run the standalone session watcher. It runs independently of any MCP client and posts a JSON payload to a webhook when a session gets stuck.

Required environment variables:

• JULES_API_KEY: Your Jules API key.

• JULES_WATCH_WEBHOOK_URL: The URL to POST the JSON payload to.

Optional environment variables:

• JULES_WATCH_INTERVAL_SECONDS: The polling interval in seconds (default: 60).

The payload structure:

{
  "id": "session_id_here",
  "title": "Session Title",
  "state": "AWAITING_PLAN_APPROVAL",
  "url": "https://jules.google.com/session_url"
}

Running the watcher:

Via npx:

JULES_API_KEY=your_key JULES_WATCH_WEBHOOK_URL=https://hooks.slack.com/services/... npx -y google-jules-mcp-server watch

Via local clone:

JULES_API_KEY=your_key JULES_WATCH_WEBHOOK_URL=https://hooks.slack.com/services/... node build/index.js watch

The watcher can also be run directly from a built checkout:

JULES_API_KEY=your_key JULES_WATCH_WEBHOOK_URL=https://your.webhook.url/here node build/watch.js

Example PM2 configuration (ecosystem.config.js):

module.exports = {
  apps: [
    {
      name: "jules-watcher",
      script: "npx",
      args: "google-jules-mcp-server watch",
      env: {
        JULES_API_KEY: "your_key",
        JULES_WATCH_WEBHOOK_URL: "https://your.webhook.url/here",
        JULES_WATCH_INTERVAL_SECONDS: "60",
      },
    },
  ],
};

Example systemd service (/etc/systemd/system/jules-watcher.service):

[Unit]
Description=Jules Session Watcher

[Service]
ExecStart=/usr/bin/npx google-jules-mcp-server watch
Environment="JULES_API_KEY=your_key"
Environment="JULES_WATCH_WEBHOOK_URL=https://your.webhook.url/here"
Restart=always

[Install]
WantedBy=multi-user.target

Example Docker one-liner:

docker run -d --name jules-watcher \
  -e JULES_API_KEY=your_key \
  -e JULES_WATCH_WEBHOOK_URL=https://your.webhook.url/here \
  node:22 npx -y google-jules-mcp-server watch

Rate Limits and Quotas

Jules enforces task quotas based on subscription tier (Free: 15 daily / 3 concurrent; Google AI Pro: ~75 daily / 15 concurrent; Google AI Ultra: ~300 daily / 60 concurrent). Tasks count against quota even if they fail, on a rolling 24-hour window.

Development

See CONTRIBUTING.md for the full setup and PR checklist, and CODE_OF_CONDUCT.md for community standards.

npm run dev              # tsc --watch
npm run lint              # eslint
npm run format             # prettier --check
npm run typecheck           # tsc --noEmit
npm test                    # vitest run
npm run test:coverage        # vitest run --coverage (enforces threshold)
npm run test:watch            # vitest
npm run inspector               # MCP Inspector — exercise tools without a full client

Testing strategy

Unit tests use MSW to intercept HTTP at the network layer rather than mocking the client module directly — this means core/http-client.ts's own logic (auth headers, retry/backoff, error mapping, Retry-After parsing) is exercised by tests, not just the handlers built on top of it. Fixtures in tests/fixtures/ encode real, previously-verified Jules API response shapes as MSW mock bodies; because the real client parses them through the Zod schemas at test time, a schema/fixture mismatch fails the test suite immediately.

tests/smoke/live-api.smoke.test.ts is an opt-in, read-only smoke test against the real Jules API (jules_list_sources only, to avoid spending task quota). It's excluded from npm test and CI, and only runs via:

JULES_LIVE_SMOKE_TEST=1 npm run test:smoke

Adding a new tool

1. Add/extend the resource's schemas.ts (Zod schema + inferred type).

2. Add the API call to that resource's client.ts.

3. Add formatting logic to format.ts and the handler + registerTool call to tools.ts.

4. Add MSW-backed tests for the client, format, and tool-handler layers.

Troubleshooting

• Tools not appearing: verify the absolute path in your client config, confirm build/index.js exists (npm run build), and restart the client completely.

• "JULES_API_KEY environment variable is required": the key isn't set in your client's server config env block.

• "No repositories connected to Jules": visit https://jules.google.com, connect your GitHub account, and grant repository access.

• 401 / 403 / 404: 401 means an invalid API key (regenerate at the settings link above), 403 means insufficient permissions or exceeded quota, 404 means the session or repository ID doesn't exist.

• Every call fails with Unexpected token '', "..." is not valid JSON: you're behind a proxy on 0.2.3 or earlier, where gzipped responses reached the parser still compressed. Upgrade to the latest release.

• Network error connecting to Jules API: fetch failed, or calls that hang: if your network requires a proxy, the server isn't seeing it. Exporting it in your shell isn't enough — your client spawns the server as a child process, so HTTPS_PROXY belongs in that server's env block. See Behind a corporate proxy.

Security

Found a vulnerability? See SECURITY.md for how to report it privately.

API Reference

• Base URL: https://jules.googleapis.com/v1alpha

• Authentication: X-Goog-Api-Key header

• Jules web app: https://jules.google.com

License

MIT

Changelog

See GitHub Releases — every published version gets an auto-generated release with notes grouped by change type.