Integrate Bazel with AI coding assistants via the Model Context Protocol
bazel-mcp is a Model Context Protocol server that exposes your Bazel workspace to AI assistants like Claude (in VS Code or Cursor). It enables AI assistants to understand and work with Bazel projects by providing direct access to build, test, run, and query capabilities.
- π€ AI-Native Development: Let AI assistants build, test, and run Bazel targets directly
- π¦ Zero Configuration: Automatically discovers all Bazel targets in your workspace
- π Real-time Streaming: See build and test output as it happens
- π― Smart Context: AI understands your build graph and dependencies
- β‘ Fast Iteration: No context switching between AI chat and terminal
pip install bazel-mcpgit clone https://github.com/sandeepnmenon/py_bazel_mcp
cd py_bazel_mcp
pip install -e .Create .vscode/mcp.json in your workspace:
{
"mcpServers": {
"bazel-mcp": {
"command": "bazel-mcp",
"args": ["--repo", "${workspaceFolder}"]
}
}
}Add as a custom MCP server:
- Settings β MCP Servers β Add Custom Server
- Command:
bazel-mcp - Args:
--repo /path/to/your/bazel/workspace
Ask your AI assistant:
"Can you list all Bazel targets in this workspace?"
The assistant should use the bazel_list_targets tool and show your project's targets.
| Tool | Description |
|---|---|
bazel_list_targets |
List all discovered targets grouped by type |
bazel_query |
Run arbitrary Bazel query expressions |
bazel_build |
Build one or more targets with streaming output |
bazel_run |
Run a binary target with arguments |
bazel_test |
Run tests with optional filters |
repo_setup |
Run project setup scripts |
bazel://targets: Returns a JSON snapshot of all discovered targets in your workspace
"Build the server binary"
# AI will use:
bazel_build(targets=["//apps:server"])"Run all tests matching 'Vector' in the math library"
# AI will use:
bazel_test(
targets=["//lib/math:all"],
flags=["--test_filter=Vector.*"]
)"What depends on the database library?"
# AI will use:
bazel_query(expr="rdeps(//..., //lib:database)")"Show me the build graph for the main app"
# AI will use:
bazel_query(expr="deps(//main:app)")"Run the CLI tool with port 8080"
# AI will use:
bazel_run(
target="//tools:cli",
args=["--port=8080"]
)bazel_list_targets - List all discovered targets
Parameters:
refresh(bool, optional): Force re-discovery of targets
Returns: JSON with targets grouped by kind (cc_library, cc_binary, py_library, py_binary, cc_test, py_test)
bazel_query - Run Bazel query expressions
Parameters:
expr(str, required): Bazel query expressionflags(list, optional): Additional Bazel flags
Example:
bazel_query(expr="deps(//main:app)")
bazel_query(expr="kind('cc_test', //...)", flags=["--output=label_kind"])bazel_build - Build targets
Parameters:
targets(list, required): Target labels to buildflags(list, optional): Bazel build flags
Example:
bazel_build(targets=["//src:lib", "//apps:server"])
bazel_build(targets=["//..."], flags=["--config=debug"])bazel_run - Run a binary target
Parameters:
target(str, required): Binary target labelargs(list, optional): Arguments for the binaryflags(list, optional): Bazel run flags
Example:
bazel_run(target="//tools:cli", args=["--port=8080"])bazel_test - Run tests
Parameters:
targets(list, optional): Test targets (default://...)flags(list, optional): Test flags
Example:
bazel_test(targets=["//tests:unit_tests"])
bazel_test(targets=["//..."], flags=["--test_filter=MyTest.*"])repo_setup - Run setup scripts
Parameters:
skipInstall(bool, optional): Skip install scripts
Runs (if present):
./tools/setup_cache.sh./install/install_all.sh
| Variable | Description | Default |
|---|---|---|
BAZEL_PATH |
Path to Bazel executable | bazel |
BAZELISK |
Use Bazelisk if available | auto-detect |
PYTHONPATH |
Python module search path | Required for source installs |
Bazelisk automatically manages Bazel versions:
# Install Bazelisk
wget -O bazelisk https://github.com/bazelbuild/bazelisk/releases/latest/download/bazelisk-linux-amd64
chmod +x bazelisk
sudo mv bazelisk /usr/local/bin/bazel
# bazel-mcp will automatically detect and use it| Issue | Solution |
|---|---|
| "No module named 'mcp'" | Install with pip install bazel-mcp |
| "Not a valid Bazel repository" | The server must be run from a directory containing WORKSPACE, WORKSPACE.bazel, or MODULE.bazel. Check your --repo path. |
| "bazel query failed" | Ensure you're in a Bazel workspace (has WORKSPACE or MODULE.bazel) |
| Editor not detecting server | Restart editor after configuration |
| Logs not streaming | Add --verbose_failures flag to see detailed output |
git clone https://github.com/sandeepnmenon/py_bazel_mcp
cd py_bazel_mcp
python -m venv .venv
source .venv/bin/activate
pip install -e .pytest tests/py_bazel_mcp/
βββ src/bazel_mcp/
β βββ __init__.py
β βββ server.py # MCP server implementation
β βββ bazel.py # Bazel command wrappers
β βββ targets.py # Target discovery & caching
β βββ util.py # Utility functions
βββ tests/ # Unit tests
βββ pyproject.toml # Package configuration
βββ README.md # Documentation
Contributions are welcome!
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
Please report issues on our GitHub Issues page. Include:
- Your environment (OS, Python version, Bazel version)
- Steps to reproduce
- Expected vs actual behavior
MIT License - see LICENSE file for details.
- Model Context Protocol - The protocol that makes this possible
- Bazel - The build system we're integrating with
- The MCP community for inspiration and examples
- Documentation: GitHub Wiki
- PyPI Package: bazel-mcp
- Issue Tracker: GitHub Issues
Built for developers using Bazel and AI assistants