MCP Builder

Build a working MCP server from a description of the tools you need. Produces a deployable Python server using FastMCP.

Workflow

Step 1: Define What to Expose

Ask what the server needs to provide:

• Tools — Functions Claude can call (API wrappers, calculations, file operations)
• Resources — Data Claude can read (database records, config, documents)
• Prompts — Reusable prompt templates with parameters

A brief like "MCP server for querying our customer database" is enough.

Step 2: Scaffold the Server

pip install fastmcp

Copy and customise assets/basic-server.py:

from fastmcp import FastMCP

# MUST be at module level for FastMCP Cloud
mcp = FastMCP("My Server")

@mcp.tool()
async def search_customers(query: str) -> str:
    """Search customers by name or email."""
    # Implementation here
    return f"Found customers matching: {query}"

@mcp.resource("customers://{customer_id}")
async def get_customer(customer_id: str) -> str:
    """Get customer details by ID."""
    return f"Customer {customer_id} details"

if __name__ == "__main__":
    mcp.run()

Step 3: Add Companion CLI Scripts (Optional)

For Claude Code terminal use, add scripts alongside the MCP server:

my-mcp-server/
├── src/index.ts          # MCP server (for Claude.ai)
├── scripts/
│   ├── search.ts         # CLI version of search tool
│   └── _shared.ts        # Shared auth/config
├── SCRIPTS.md            # Documents available scripts
└── package.json

CLI scripts provide file I/O, batch processing, and richer output that MCP can't.
See assets/SCRIPTS-TEMPLATE.md and assets/script-template.ts for TypeScript templates.

Step 4: Test Locally

# Run server directly
python server.py

# With FastMCP dev mode (auto-reload)
fastmcp dev server.py

# HTTP mode for remote clients
python server.py --transport http --port 8000

# Test with MCP Inspector
fastmcp dev server.py --with-editable .

Step 5: Deploy

FastMCP Cloud (simplest):

fastmcp deploy server.py --name my-server

Docker (self-hosted):
See references/cloud-deployment.md for Dockerfile patterns.

Cloudflare Workers (edge):
See the cloudflare-worker-builder skill for Workers-based MCP servers.

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Critical Patterns

Module-Level Server Instance

FastMCP Cloud requires the server instance at module level:

# CORRECT
mcp = FastMCP("My Server")

@mcp.tool()
def my_tool(): ...

# WRONG — Cloud can't find the server
def create_server():
    mcp = FastMCP("My Server")
    return mcp

Type Annotations Required

FastMCP uses type annotations to generate tool schemas:

@mcp.tool()
async def search(
    query: str,           # Required parameter
    limit: int = 10,      # Optional with default
    tags: list[str] = []  # Complex types supported
) -> str:
    """Docstring becomes the tool description."""
    ...

Error Handling

Return errors as strings, don't raise exceptions:

@mcp.tool()
async def get_data(id: str) -> str:
    try:
        result = await fetch_data(id)
        return json.dumps(result)
    except NotFoundError:
        return f"Error: No data found for ID {id}"

---

Asset Files

• assets/basic-server.py — Minimal FastMCP server template
• assets/self-contained-server.py — Server with storage and middleware
• assets/tools-examples.py — Tool patterns and type annotations
• assets/resources-examples.py — Resource URI patterns
• assets/prompts-examples.py — Prompt template patterns
• assets/client-example.py — MCP client usage
• assets/SCRIPTS-TEMPLATE.md — CLI companion docs template
• assets/script-template.ts — TypeScript CLI script template

Reference Files

• references/common-errors.md — 30+ documented errors with fixes
• references/cli-commands.md — FastMCP CLI reference
• references/cloud-deployment.md — Deployment patterns (Cloud, Docker, Workers)
• references/production-patterns.md — Auth, middleware, storage backends
• references/integration-patterns.md — FastAPI mount, OpenAPI import
• references/context-features.md — Lifespan, dependency injection