Jules
Jules async coding agent - run autonomous tasks using Jules
Jules MCP Server (jules-mcp)
An MCP (Model Context Protocol) server that exposes Google Jules Agent operations via FastMCP.
This server lets MCP-compatible clients (and Python code) list Jules sources, create and manage sessions, and inspect activities using the official jules-agent-sdk.
- Server framework: FastMCP
- SDK: jules-agent-sdk
- Python: 3.13+
- License: Apache-2.0
Features
Tools exposed via the MCP server (grouped by area):
- Sources
- get_source(source_id)
- list_sources(filter_str=None, page_size=None, page_token=None)
- get_all_sources(filter_str=None)
- Sessions
- create_session(prompt, source, starting_branch=None, title=None, require_plan_approval=False)
- get_session(session_id)
- list_sessions(page_size=None, page_token=None)
- approve_session_plan(session_id)
- send_session_message(session_id, prompt)
- wait_for_session_completion(session_id, poll_interval=5, timeout=600)
- Activities
- get_activity(session_id, activity_id)
- list_activities(session_id, page_size=None, page_token=None)
- list_all_activities(session_id)
See jules_mcp/jules_mcp.py for signatures and inline docstrings.
Installation
Option A — from a local checkout:
# from the repository root
pip install -e .
Option B — using uv (recommended during development):
# from the repository root
uv sync
The project targets Python 3.13+.
Configuration
Set your Jules API key via environment variable:
- Windows PowerShell
$Env:JULES_API_KEY = "<your_api_key_here>" - Unix shells (bash/zsh)
export JULES_API_KEY="<your_api_key_here>"
If you do not provide an argument to jules(), the SDK reads JULES_API_KEY automatically.
Running the MCP server
There are two common ways to run the server.
- Programmatic run (in-process) using FastMCP Client — useful for testing or embedding:
import asyncio
from fastmcp import Client
from jules_mcp import mcp
async def main():
async with Client(mcp) as client:
# Example: list all sources (auto-paginated)
result = await client.call_tool("get_all_sources")
print(result)
asyncio.run(main())
- As a standalone MCP server executable for external MCP clients:
-
Using uv and FastMCP directly
uv run fastmcp run jules_mcp/jules_mcp.py:mcpThis starts the MCP server over stdio.
-
Using the provided configuration files
- MCP.json: a sample command configuration for MCP-aware hosts.
- fastmcp.json: FastMCP runtime/environment configuration.
Adjust paths in MCP.json if you use a different checkout location.
You can also run via the module entry point:
python -m jules_mcp
This calls start_mcp() which invokes FastMCP.run() using the "mcp" instance defined in the package.
Usage notes and examples
- Listing and filtering sources
import asyncio
from fastmcp import Client
from jules_mcp import mcp
async def main():
async with Client(mcp) as client:
# Filter syntax follows AIP-160 filtering rules supported by Jules
res = await client.call_tool(
"list_sources",
{"filter_str": "name=sources/source1 OR name=sources/source2", "page_size": 10}
)
print(res)
asyncio.run(main())
- Creating a session and waiting for completion
import asyncio
from fastmcp import Client
from jules_mcp import mcp
async def run_session():
async with Client(mcp) as client:
session = await client.call_tool(
"create_session",
{
"prompt": "Analyze the repository and propose improvements",
"source": "sources/abc123",
"require_plan_approval": True,
},
)
# Optionally approve plan
await client.call_tool("approve_session_plan", {"session_id": session["name"]})
# Wait for completion
final = await client.call_tool(
"wait_for_session_completion",
{"session_id": session["name"], "poll_interval": 5, "timeout": 600}
)
print(final)
asyncio.run(run_session())
- Inspecting activities
import asyncio
from fastmcp import Client
from jules_mcp import mcp
async def list_acts(session_id: str):
async with Client(mcp) as client:
acts = await client.call_tool("list_all_activities", {"session_id": session_id})
for a in acts:
print(a)
asyncio.run(list_acts("sessions/abc123"))
Development
-
Create a virtual environment and install dev dependencies
uv sync # or: pip install -e .[dev] -
Run tests (note: some tools may reach the Jules API and require JULES_API_KEY)
uv run pytest -q -
Linting/formatting: follow your preferred tools; this repo does not include linters by default.
Project metadata
- Package name: jules-mcp
- Version: 0.1.0
- Entry points:
- Python module: python -m jules_mcp
- FastMCP source: jules_mcp/jules_mcp.py:mcp
License
Apache License 2.0. See the LICENSE file for details.
Acknowledgements
- FastMCP — https://gofastmcp.com/
- Model Context Protocol — https://modelcontextprotocol.io/
- jules-agent-sdk — unofficial/official SDK used by this server
관련 서버
Scout Monitoring MCP
스폰서Put performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
스폰서Access financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
4o-image
Generate and edit images using text prompts with the 4o-image API.
Squidler.io
Squidler is designed to validate your web app as a human based on natural language use cases, without write brittle, DOM-dependent tests.
Background Process MCP
A server that provides background process management capabilities, enabling LLMs to start, stop, and monitor long-running command-line processes.
FastMCP ThreatIntel
An AI-powered threat intelligence analysis tool for multi-source IOC analysis, APT attribution, and interactive reporting.
Trade-MCP
A modular trading automation project using the Zerodha Kite Connect API for tool-based and resource-based automation.
Digma
A code observability MCP enabling dynamic code analysis based on OTEL/APM data to assist in code reviews, issues identification and fix, highlighting risky code etc.
Databutton App MCP
Call your Databutton app endpoints as LLM tools with MCP.
MCP-Insomnia
An MCP server for AI agents to create and manage API collections in Insomnia-compatible format.
Image Generator MCP Server
Generate placeholder images with specified dimensions and colors, and save them to a file path.
Storybook MCP
A universal MCP server that connects to any Storybook site and extracts documentation in real-time using Playwright. Use it with any AI or client that supports MCP (Model Context Protocol)—Cursor, Claude Desktop, Windsurf, or other MCP hosts.