A Model Context Protocol (MCP) server that integrates with Tilt to provide programmatic access to Tilt resources and logs through LLM applications.

Imagine prompting like this:

Please work on {some LLM request} and then check tilt MCP for "backend-api" resource logs for compile status. Make sure that "backend-tests" resource is successful with your changes.

The key insight is you no longer need to tell your LLM how to build and deploy your code. Instead, you can simply ask it to what to build and deploy.

Tilt is a powerful tool for working with Docker/Kubernetes workloads. With the Tilt MCP server, you can integrate Tilt's features directly into your workflow using Large Language Models (LLMs) like Claude Code / Codex / Gemini / VS Code Copilot / etc.

This saves significant LLM tokens (and so ⏱️+💰), both by avoiding to give extra context to your LLM on how to build/deploy, and also by avoiding LLMs actually doing the build/deploy. All the LLM needs to know is to make code changes then call the tilt MCP server to get real-time feedback.

The Tilt MCP server allows Large Language Models (LLMs) and AI assistants to interact with your Tilt development environment. It provides tools to:

• List all enabled Tilt resources
• Fetch logs from specific resources
• Monitor resource status and health
• Enable and disable resources dynamically
• Get detailed information about resources
• Trigger resource rebuilds
• Wait for resources to reach specific conditions

This enables AI-powered development workflows, debugging assistance, automated monitoring, and intelligent resource management of your Tilt-managed services.

The Tilt MCP server follows the Model Context Protocol specification and exposes three types of capabilities:

Resources provide read-only access to Tilt data. They're automatically discovered by MCP clients and can be accessed via their URI.

Example URIs:

• tilt://resources/all - Get all resources
• tilt://resources/frontend/logs - Get last 1000 lines from frontend (default)
• tilt://resources/frontend/logs?tail=100 - Get last 100 lines from frontend
• tilt://resources/backend/describe - Get detailed info about backend

Tools enable LLMs to perform actions that modify the state of your Tilt environment.

Prompts are reusable templates that guide the LLM through common debugging and troubleshooting workflows.

All capabilities include comprehensive error handling:

• Resource Not Found: Raises ValueError with helpful message
• Tilt Connection Issues: Raises RuntimeError with Tilt error details
• JSON Parsing Errors: Provides detailed parsing error information

All operations are logged to ~/.tilt-mcp/tilt_mcp.log for debugging.

MCP Protocol Compliance:

• 🔍 Resources: Read-only access to Tilt data via URI templates (e.g., tilt://resources/all)
• 🛠️ Tools: Actions with side effects for resource management and control
• 💡 Prompts: Guided workflows for debugging and troubleshooting

Capabilities:

• 📊 Resource Discovery: List all active Tilt resources with their current status
• 📜 Log Retrieval: Fetch recent logs from any Tilt resource with configurable tail
• 🔄 Resource Triggering: Manually trigger Tilt resources to rebuild/update
• ✅ Resource Control: Enable or disable resources dynamically
• 📋 Detailed Information: Get comprehensive details about any resource
• ⏳ Wait Conditions: Wait for resources to reach specific states
• 🤖 Guided Workflows: Pre-built prompts for common debugging scenarios

Technical Features:

• 🛡️ Type Safety: Built with Python type hints for better IDE support
• 🚀 Async Support: Fully asynchronous implementation using FastMCP
• 📈 MCP Best Practices: Proper separation of resources, tools, and prompts
• 🔧 Comprehensive Logging: All operations logged to ~/.tilt-mcp/tilt_mcp.log

• Python 3.10 or higher (required by FastMCP 2.0)
• Tilt installed and configured
• An MCP-compatible client (e.g., Claude Desktop, mcp-cli)

You can install Tilt MCP in three ways:

The Docker-based installation requires no Python setup and is automatically kept up-to-date with monthly builds. The image is optimized for size using Alpine Linux (~320MB vs 545MB+ for Debian-based images - 41% reduction).

How it works:

• Automatically discovers the Tilt API port from ~/.tilt-dev/config based on TILT_PORT (web UI port)
• Uses socat to dynamically create a TCP tunnel from inside the container to the host Tilt server
• Your host's ~/.tilt-dev directory is mounted with write access (Tilt CLI needs lock files)
• Supports multiple Tilt instances running on different ports (10350, 10351, etc.)
• The Python code handles port discovery and socat management automatically

Note: The image size is primarily driven by FastMCP 2.0's dependencies (cryptography, pydantic, etc.). For reference:

• Base Alpine + Python: ~50MB
• Tilt binary: ~20MB
• FastMCP 2.0 + dependencies: ~250MB

See the MCP Configuration section below for setup instructions.

pip install tilt-mcp

Best for: Linux users or when you prefer local installation

git clone https://github.com/rrmistry/tilt-mcp.git
cd tilt-mcp
pip install -e .

Best for: Development or testing local changes

Add the following to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json Linux: ~/.config/claude/claude_desktop_config.json

For macOS/Linux (single Tilt instance on default port 10350):

{
  "mcpServers": {
    "tilt": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "${HOME}/.tilt-dev:/home/mcp-user/.tilt-dev",
        "-v",
        "${HOME}/.tilt-mcp:/home/mcp-user/.tilt-mcp",
        "--network=host",
        "ghcr.io/rrmistry/tilt-mcp:latest"
      ],
      "env": {}
    }
  }
}

For multiple Tilt instances (example with port 10351):

{
  "mcpServers": {
    "tilt-project1": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "${HOME}/.tilt-dev:/home/mcp-user/.tilt-dev",
        "-v",
        "${HOME}/.tilt-mcp:/home/mcp-user/.tilt-mcp",
        "-e",
        "TILT_PORT=10350",
        "--network=host",
        "ghcr.io/rrmistry/tilt-mcp:latest"
      ],
      "env": {}
    },
    "tilt-project2": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "${HOME}/.tilt-dev:/home/mcp-user/.tilt-dev",
        "-v",
        "${HOME}/.tilt-mcp:/home/mcp-user/.tilt-mcp",
        "-e",
        "TILT_PORT=10351",
        "--network=host",
        "ghcr.io/rrmistry/tilt-mcp:latest"
      ],
      "env": {}
    }
  }
}

For Windows (PowerShell):

{
  "mcpServers": {
    "tilt": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-v",
        "${env:USERPROFILE}\\.tilt-dev:/home/mcp-user/.tilt-dev",
        "-v",
        "${env:USERPROFILE}\\.tilt-mcp:/home/mcp-user/.tilt-mcp",
        "--network=host",
        "ghcr.io/rrmistry/tilt-mcp:latest"
      ],
      "env": {}
    }
  }
}

For Windows (CMD): Use %USERPROFILE% instead of ${env:USERPROFILE} in the volume mount paths.

Key Configuration Notes:

• TILT_PORT represents the web UI port (10350, 10351, etc.) - NOT the API port
• The Python code auto-discovers the actual API port from ~/.tilt-dev/config
• Context naming: port 10350 → "tilt-default", port 10351 → "tilt-10351", etc.
• The ~/.tilt-dev directory must be mounted with write access (Tilt CLI needs lock files)
• socat dynamically forwards the discovered API port to host.docker.internal
• --network=host is required for host.docker.internal to work on macOS/Windows

If you installed via PyPI or from source, use this simpler configuration:

{
  "mcpServers": {
    "tilt": {
      "command": "tilt-mcp"
    }
  }
}

Making sure that tilt-mcp is in your PATH.

You can run the server directly:

python -m tilt_mcp.server

Or use it with the MCP CLI:

mcp run python -m tilt_mcp.server

To check the installed version of tilt-mcp:

tilt-mcp --version

Build the optimized Alpine-based image:

docker build -t ghcr.io/rrmistry/tilt-mcp:latest .

Or build with a specific Tilt version:

docker build --build-arg TILT_VERSION=0.35.2 -t ghcr.io/rrmistry/tilt-mcp:latest .

To use Debian instead of Alpine (larger image but better compatibility):

docker build --build-arg BASE_IMAGE=python:3.11-slim-bookworm -t ghcr.io/rrmistry/tilt-mcp:latest .

Once configured, the Tilt MCP server provides Resources, Tools, and Prompts through the Model Context Protocol.

Resources are read-only and provide direct access to Tilt data. MCP clients can access them via their URI:

Get all resources:

tilt://resources/all

Returns:

{
  "resources": [
    {
      "name": "frontend",
      "type": "k8s",
      "status": "ok",
      "updateStatus": "ok"
    },
    {
      "name": "backend-api",
      "type": "k8s",
      "status": "pending",
      "updateStatus": "pending"
    }
  ],
  "count": 2
}

Get logs from a resource:

tilt://resources/frontend/logs

Returns the last 1000 lines of logs as plain text (default).

Get custom number of log lines:

tilt://resources/frontend/logs?tail=50

Returns the last 50 lines of logs as plain text.

Get detailed resource information:

tilt://resources/backend/describe

Returns detailed YAML/text output with configuration, status, and build history.

Tools perform actions that modify the state of your Tilt environment.

Trigger a rebuild:

{
  "name": "trigger_resource",
  "arguments": {
    "resource_name": "backend"
  }
}

Enable specific resources:

{
  "name": "enable_resource",
  "arguments": {
    "resource_names": ["frontend", "backend"],
    "enable_only": false
  }
}

Disable resources:

{
  "name": "disable_resource",
  "arguments": {
    "resource_names": ["frontend", "backend"]
  }
}

Wait for a resource to be ready:

{
  "name": "wait_for_resource",
  "arguments": {
    "resource_name": "backend",
    "condition": "Ready",
    "timeout_seconds": 60
  }
}

Prompts provide guided workflows for common tasks. They generate contextual messages that guide the LLM through debugging and troubleshooting.

Debug a failing resource:

{
  "name": "debug_failing_resource",
  "arguments": {
    "resource_name": "backend"
  }
}

This generates a comprehensive debugging workflow that guides the LLM to check logs, status, and suggest fixes.

Perform a health check:

{
  "name": "health_check_all_resources",
  "arguments": {}
}

This creates a systematic health check workflow across all resources.

Optimize resource usage:

{
  "name": "optimize_resource_usage",
  "arguments": {
    "focus_resources": ["backend", "database"]
  }
}

This guides the LLM to enable only specified resources and disable others to conserve system resources.

Here are some example prompts you can use with an AI assistant that has access to this MCP server:

Using Built-in Prompt Templates:

• "Use the debug_failing_resource prompt for the backend service"
• "Run a health check on all my resources"
• "Use the troubleshoot_startup_failure prompt to investigate why the frontend won't start"
• "Analyze the logs from the backend service using the analyze_resource_logs prompt"
• "Help me optimize my resources to focus on just the backend and database"

Resource Discovery & Status:

• "Show me all the Tilt resources that are currently running"
• "Which services are failing or have errors?"
• "Compare the status of frontend and backend services"
• "Access the tilt://resources/all resource to see all services"

Log Analysis:

• "Get the last 100 lines of logs from the backend-api service"
• "Read the logs from tilt://resources/frontend/logs?tail=50"
• "Show me the last 200 lines of logs from any failing services"
• "Help me debug why the frontend service is crashing by looking at recent logs"

Resource Control:

• "Disable the frontend and backend services"
• "Enable only the database service and disable everything else"
• "Enable the frontend service"
• "Disable all non-essential services to save resources"

Build & Deployment:

• "Trigger a rebuild of the backend service"
• "Rebuild the frontend and show me the logs"
• "Trigger all services that have errors"
• "Wait for the backend to be ready before checking its logs"

Advanced Automation Workflows:

• "Enable the backend, wait for it to be ready, then check its logs"
• "Disable all services, then enable only frontend and wait for it to start"
• "Get detailed info about the database and show me its recent logs"
• "Trigger a rebuild of the API service and wait until it's ready"
• "Run a complete health check and fix any issues you find"

Using Resources Directly:

• "Read tilt://resources/backend/describe to understand the configuration"
• "Compare logs from tilt://resources/frontend/logs?tail=500 and tilt://resources/backend/logs?tail=500"
• "Check tilt://resources/all to see which services need attention"
• "Get the last 50 lines from the frontend: tilt://resources/frontend/logs?tail=50"

# Clone the repository
git clone https://github.com/yourusername/tilt-mcp.git
cd tilt-mcp

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode with dev dependencies
pip install -e ".[dev]"

pytest

# Format code
black src tests

# Run linter
ruff check src tests

# Type checking
mypy src

1. "Tilt not found" error

   • Ensure Tilt is installed and available in your PATH
   • Try running tilt version to verify installation

2. "No resources found" when Tilt is running

   • Make sure your Tiltfile is loaded and resources are started
   • Check that you're running the MCP server in the correct directory

3. Connection errors

   • Verify the MCP client configuration is correct
   • Check the logs at ~/.tilt-mcp/tilt_mcp.log

4. Docker based tilt-mcp not able to connect

   • Ensure your ~/.tilt-dev directory exists and is being created by your Tilt instance
   • The directory must be mounted with write access: ~/.tilt-dev:/home/mcp-user/.tilt-dev (Tilt CLI needs lock files)
   • TILT_PORT should be your web UI port (10350, 10351, etc.), not the random API port
   • Check the logs at ~/.tilt-mcp/tilt_mcp.log to see the discovered API port
   • The Python code auto-discovers the API port from the config and launches socat automatically
   • Ensure --network=host is included in docker args (required for host.docker.internal)

5. Alpine Linux compatibility

   • The Docker image uses Alpine Linux for size optimization
   • Most Python packages work fine, but if you encounter issues with binary dependencies, you can build using the Debian base by changing the BASE_IMAGE build arg to python:3.11-slim-bookworm

The MCP server logs all operations to ~/.tilt-mcp/tilt_mcp.log. The log includes:

• Server startup/shutdown events
• Resource fetch operations
• Log retrieval operations
• Error messages with full details

To enable debug logging, set the environment variable:

export LOG_LEVEL=DEBUG

Log Format: timestamp - logger_name - level - message

Viewing Logs:

# View recent logs
tail -f ~/.tilt-mcp/tilt_mcp.log

# Search for errors
grep ERROR ~/.tilt-mcp/tilt_mcp.log

# View logs from a specific resource fetch
grep "get_all_resources" ~/.tilt-mcp/tilt_mcp.log

We welcome contributions! Please see our Contributing Guide for details on:

• Setting up your development environment
• Running tests
• Submitting pull requests
• Code style guidelines

This project is licensed under the MIT License - see the LICENSE file for details.

• Built with FastMCP for the MCP server implementation
• Integrates with Tilt for Kubernetes development

• 📧 Email: [email protected]
• 💬 Issues: GitHub Issues