| name | fastmcp-builder |
| description | Build production-ready MCP servers using FastMCP framework with proven patterns for tools, resources, prompts, OAuth authentication, and comprehensive testing. Use this when creating FastMCP-based MCP servers with features like Google OAuth, multiple resource types, testing with FastMCP Client, or complex tool implementations. |
FastMCP Builder - Production MCP Server Development
Overview
This skill provides comprehensive, production-ready patterns for building MCP (Model Context Protocol) servers using FastMCP, the official high-level Python framework. It includes complete reference implementations, working examples, and best practices proven in production.
FastMCP is the recommended approach for building MCP servers in Python - it's simpler, faster to develop, and more maintainable than the low-level MCP SDK.
What's Included
This skill contains:
- Reference Documentation (
reference/) - 6 comprehensive guides covering all aspects of FastMCP development - Code Examples (
examples/) - Runnable examples from minimal to complete servers - Complete Reference Project (
reference-project/) - Full production implementation with:- 6 production-ready tools
- 7 resource instances (4 types)
- 1 universal prompt
- 145 passing tests
- OAuth integration
- Complete documentation
💡 Tip: When in doubt, look at the reference-project for real-world implementation examples.
When to Use This Skill
Use this skill when you need to:
✅ Build MCP servers with FastMCP - Python-based MCP server development ✅ Add OAuth authentication - Especially Google OAuth for remote access ✅ Implement production patterns - Tools, resources, prompts with best practices ✅ Set up comprehensive testing - Using FastMCP Client for fast, in-memory tests ✅ Structure larger projects - Proper organization and separation of concerns ✅ Deploy to production - With authentication, error handling, monitoring
Don't use this skill for:
- ❌ TypeScript/Node.js MCP servers (use mcp-builder skill instead)
- ❌ Low-level MCP protocol work (use MCP SDK directly)
- ❌ Non-FastMCP Python servers (this is FastMCP-specific)
Consulting Official Documentation
IMPORTANT: When encountering questions or issues not covered in this skill's reference materials, you should:
Primary Method: Use WebSearch (Recommended)
The most reliable way to find FastMCP documentation is using WebSearch with site-specific queries:
WebSearch(
query="site:gofastmcp.com [your specific topic]"
)
This will search the official FastMCP documentation site and return relevant pages.
Alternative: Direct Page Access
If you know the general documentation structure, you can fetch specific pages directly:
WebFetch(
url="https://gofastmcp.com/[section]/[topic]",
prompt="Your specific question about this topic"
)
Common documentation sections:
/getting-started/- Installation, quickstart, welcome/servers/- Tools, resources, prompts, context, logging/deployment/- Running servers, HTTP deployment, configuration/integrations/- Auth0, AWS Cognito, Azure, GitHub, Google, WorkOS, OpenAI, etc./testing/- Testing guides and best practices
Tip: Any page can be accessed as markdown by appending .md to the URL.
When to Consult Official Docs
Consult official documentation when:
- You encounter a feature or API not covered in this skill's references
- You need the latest updates or breaking changes
- User asks about FastMCP capabilities you're unsure about
- You're implementing advanced patterns not in the reference materials
- There are version-specific behaviors or deprecations
- You need clarification on authentication providers beyond Google OAuth
- You want to verify current best practices
Example Workflows
User asks about OpenAI integration:
WebSearch(query="site:gofastmcp.com openai integration") → Find https://gofastmcp.com/integrations/openai → Fetch that page for detailsUser asks about AWS Cognito authentication:
WebSearch(query="site:gofastmcp.com aws cognito oauth") → Find relevant auth documentation → Implement based on official guidanceUser asks about testing patterns:
WebSearch(query="site:gofastmcp.com testing") → Find testing documentation → Apply patterns from official docsExploring what's available:
WebSearch(query="site:gofastmcp.com deployment options") WebSearch(query="site:gofastmcp.com authentication providers") → Browse results to see available topics
Note: Always try the reference materials in this skill first, then consult official docs if needed.
Workflow - Building a FastMCP Server
Phase 1: Planning & Setup
Step 1.1: Review FastMCP Overview
- Load fastmcp_overview.md
- Understand FastMCP vs MCP SDK
- Confirm FastMCP is right choice (it usually is)
Step 1.2: Understand Requirements
- What tools does the server need?
- Do you need OAuth authentication?
- Will you have resources? Prompts?
- What's the deployment target?
Step 1.3: Review Project Structure
- Load project_structure.md
- Understand the recommended directory layout
- Learn about the common.py pattern (DRY principle)
- Understand dual-mode pattern (with/without OAuth)
Step 1.4: Set Up Project
Create project structure:
mkdir my-mcp-server
cd my-mcp-server
# Create directories
mkdir -p app/tools app/resources app/prompts tests
# Create initial files
touch app/__init__.py
touch app/main.py
touch app/main_noauth.py
touch app/common.py
touch app/config.py
touch tests/__init__.py
touch pyproject.toml
touch .env.example
touch README.md
Initialize with uv:
# Install FastMCP
uv add fastmcp==2.13.0.1
uv add python-dotenv==1.2.1
# Add test dependencies
uv add --optional test pytest==8.4.2 pytest-asyncio==1.2.0 pytest-mock==3.15.1 httpx==0.28.1
Phase 2: Core Implementation
Step 2.1: Implement Configuration
Create app/config.py based on patterns in project_structure.md:
- Environment variable loading
- Configuration class with validation
- OAuth settings (if needed)
- Server metadata
Step 2.2: Implement Tools
Load tool_patterns.md for comprehensive patterns:
Identify tool patterns needed:
- Basic sync tools (health checks, simple queries)
- Data processing tools (analysis, transformation)
- Tools with Context (logging, progress)
- Stateful tools (if state management needed)
- API integration tools (external services)
Create tools in
app/tools/:- One file per tool or logical group
- Follow patterns from tool_patterns.md
- Use proper error handling
- Add comprehensive docstrings
Example tool structure:
# app/tools/my_tool.py
async def my_tool(param: str, ctx: Context | None = None) -> dict:
"""
Tool description
Args:
param: Parameter description
ctx: FastMCP context (auto-injected)
Returns:
dict: Result structure
"""
try:
if ctx:
await ctx.info("Processing...")
# Tool logic here
result = process(param)
if ctx:
await ctx.info("Completed!")
return {"status": "success", "data": result}
except Exception as e:
if ctx:
await ctx.error(f"Failed: {e}")
return {"status": "error", "error": str(e)}
Step 2.3: Implement Resources (if needed)
Load resource_patterns.md for all resource types:
Choose resource types:
- Static resources (status, features, documentation)
- Dynamic resources (generated content)
- Template resources (with path parameters)
- Wildcard resources (multi-segment paths)
Create resources in
app/resources/:- static.py for static resources
- Separate files for dynamic/template/wildcard
Example resource:
# app/resources/welcome.py
def get_welcome_message() -> str:
"""Welcome message resource"""
return "Welcome to my MCP server!"
Step 2.4: Implement Prompts (if needed)
Create reusable prompt templates:
# app/prompts/explain.py
def explain_concept(
concept: str,
audience_level: str = "intermediate",
) -> str:
"""Generate explanation prompt"""
return f"Explain {concept} for {audience_level} audience..."
Step 2.5: Create Common Registration
In app/common.py, register all components:
from fastmcp import FastMCP
# Import tools
from app.tools.my_tool import my_tool
# Import resources
from app.resources.welcome import get_welcome_message
# Import prompts
from app.prompts.explain import explain_concept
def register_all(mcp: FastMCP) -> None:
"""Register all components - DRY principle"""
# Tools
mcp.tool()(my_tool)
# Resources
mcp.resource("greeting://welcome")(get_welcome_message)
# Prompts
mcp.prompt()(explain_concept)
Step 2.6: Create Server Entry Points
app/main_noauth.py (for local development):
from fastmcp import FastMCP
from app.config import Config
from app.common import register_all
mcp = FastMCP(Config.SERVER_NAME)
register_all(mcp)
if __name__ == "__main__":
mcp.run()
app/main.py (with OAuth - if needed): Load oauth_integration.md for complete OAuth setup.
Phase 3: OAuth Integration (if needed)
Only if you need remote access with authentication.
Step 3.1: Set Up Google OAuth
Follow oauth_integration.md:
- Create OAuth Client in Google Cloud Console
- Configure environment variables (.env)
- Implement GoogleProvider in main.py
- Set up ngrok for testing
- Configure Claude Desktop Connectors
Step 3.2: Test OAuth Flow
- Start ngrok
- Start server with base-url
- Connect Claude Desktop
- Verify authentication works
Phase 4: Testing
Step 4.1: Set Up Test Structure
Load testing_guide.md for comprehensive testing patterns.
Create tests/conftest.py:
import pytest
from fastmcp import Client
from app.main_noauth import mcp
@pytest.fixture
async def client():
"""Provide FastMCP client for testing"""
async with Client(mcp) as c:
yield c
Step 4.2: Write Tool Tests
# tests/test_tools.py
@pytest.mark.asyncio
async def test_my_tool(client):
"""Should execute my_tool successfully"""
result = await client.call_tool("my_tool", {"param": "test"})
assert result.data["status"] == "success"
Step 4.3: Write Resource Tests
# tests/test_resources.py
@pytest.mark.asyncio
async def test_welcome_resource(client):
"""Should read welcome resource"""
content = await client.read_resource("greeting://welcome")
assert "Welcome" in content
Step 4.4: Write Integration Tests
# tests/test_integration.py
@pytest.mark.asyncio
async def test_complete_workflow(client):
"""Should execute complete workflow"""
# Test multiple components working together
pass
Step 4.5: Run Tests
# Run all tests
uv run pytest tests/ -v
# Run with coverage
uv run pytest tests/ --cov=app --cov-report=html
Phase 5: Documentation & Deployment
Step 5.1: Write README
Document:
- Project description
- Features
- Quick start guide
- OAuth setup (if applicable)
- Usage examples
- Testing instructions
- Deployment guide
Step 5.2: Prepare for Deployment
Environment Variables:
- Create .env.example template
- Document all required variables
- Never commit .env to git
Testing:
- Ensure all tests pass
- Test OAuth flow (if applicable)
- Test in production-like environment
Deployment:
- Choose platform (Railway, Fly.io, VPS)
- Set up HTTPS (required for OAuth)
- Configure environment variables
- Deploy and test
Reference Documentation
Load these as needed during development:
Core References
- fastmcp_overview.md - FastMCP introduction, when to use, key features
- project_structure.md - Recommended structure, file organization, patterns
Implementation Guides
- tool_patterns.md - 6 tool patterns with complete examples
- resource_patterns.md - 4 resource types (static, dynamic, template, wildcard)
- oauth_integration.md - Complete Google OAuth setup guide
- testing_guide.md - FastMCP Client testing, patterns, best practices
Example Code
Run or reference these complete examples:
- minimal_server.py - Absolute simplest FastMCP server
- complete_server_structure.py - Full-featured single-file example
- test_examples.py - Comprehensive testing examples
Quick Start Examples
Example 1: Minimal Server
from fastmcp import FastMCP
mcp = FastMCP("my-server")
@mcp.tool()
def greet(name: str) -> str:
"""Greet someone"""
return f"Hello, {name}!"
if __name__ == "__main__":
mcp.run()
Example 2: Server with Multiple Components
from fastmcp import FastMCP, Context
mcp = FastMCP("my-server")
# Tool
@mcp.tool()
async def process(text: str, ctx: Context | None = None) -> dict:
if ctx:
await ctx.info("Processing...")
return {"result": text.upper()}
# Resource
@mcp.resource("greeting://hello")
def get_greeting() -> str:
return "Hello from resource!"
# Prompt
@mcp.prompt()
def explain(topic: str) -> str:
return f"Explain {topic} in detail"
if __name__ == "__main__":
mcp.run()
Example 3: With OAuth
from fastmcp import FastMCP
from fastmcp.server.auth.providers.google import GoogleProvider
import os
auth = GoogleProvider(
client_id=os.getenv("GOOGLE_CLIENT_ID"),
client_secret=os.getenv("GOOGLE_CLIENT_SECRET"),
base_url="https://your-server.com",
)
mcp = FastMCP("my-server", auth=auth)
# ... add tools, resources, prompts ...
if __name__ == "__main__":
mcp.run(transport="http", host="0.0.0.0", port=8000)
Best Practices Summary
- ✅ Use FastMCP - Simpler than MCP SDK for most use cases
- ✅ Follow project structure - Use common.py pattern (DRY)
- ✅ Dual-mode servers - main.py (OAuth) + main_noauth.py (local)
- ✅ Comprehensive testing - Use FastMCP Client, aim for >80% coverage
- ✅ Clear documentation - Docstrings, README, usage examples
- ✅ Error handling - Graceful failures, informative error messages
- ✅ Context usage - Logging, progress for better UX
- ✅ Security - Environment variables, never commit secrets
Common Workflows
Creating a New Tool
- Create
app/tools/my_tool.py - Implement tool function
- Add to
app/common.pyregistration - Write tests in
tests/test_tools.py - Run tests:
uv run pytest tests/test_tools.py -v
Adding OAuth
- Review oauth_integration.md
- Set up Google OAuth credentials
- Update
app/config.pywith OAuth settings - Modify
app/main.pyto use GoogleProvider - Test with ngrok
- Configure Claude Desktop Connectors
Debugging
- Use
main_noauth.pyfor faster local testing - Add logging with Context:
await ctx.debug(...) - Write tests to isolate issues
- Check tool/resource registration in
common.py - Verify environment variables loaded
Additional Resources
- FastMCP Documentation: https://gofastmcp.com/
- FastMCP GitHub: https://github.com/jlowin/fastmcp
- MCP Specification: https://modelcontextprotocol.io/
- Google OAuth Guide: https://developers.google.com/identity/protocols/oauth2
Notes
- This skill focuses on FastMCP, not the low-level MCP SDK
- All examples use Python 3.11+
- OAuth examples use Google OAuth (other providers possible)
- Testing uses FastMCP Client (in-memory, fast)
- Deployment examples are production-ready
Happy building! 🚀