mcp-builder

What this skill does

# 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

```bash
pip install fastmcp
```

Create the server file. The server instance MUST be at module level:

```python
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

**Quick test -- run directly:**

```bash
python server.py
```

**Dev mode with inspector UI (recommended):**

```bash
fastmcp dev server.py
# Opens inspector at http://localhost:5173
# Hot reload, detailed logging, tool/resource inspection
```

**HTTP mode for remote clients:**

```bash
python server.py --transport http --port 8000
```

**Automated test script using FastMCP Client:**

```python
import asyncio
from fastmcp import Client

async def test_server(server_path):
    async with Client(server_path) as client:
        # List everything
        tools = await client.list_tools()
        resources = await client.list_resources()
        prompts = await client.list_prompts()

        print(f"Tools: {[t.name for t in tools]}")
        print(f"Resources: {[r.uri for r in resources]}")
        print(f"Prompts: {[p.name for p in prompts]}")

        # Call first tool
        if tools:
            result = await client.call_tool(tools[0].name, {})
            print(f"Tool result: {result}")

        # Read first resource
        if resources:
            data = await client.read_resource(resources[0].uri)
            print(f"Resource data: {data}")

asyncio.run(test_server("server.py"))
```

### Step 5: Pre-Deploy Checklist

Run these checks before deploying. All required checks must pass.

**Required (will cause deploy failure):**

1. Server file exists
2. Python syntax valid: `python3 -m py_compile server.py`
3. Module-level server object (not inside a function):
   ```bash
   grep -q "^mcp = FastMCP\|^server = FastMCP\|^app = FastMCP" server.py
   ```
4. `requirements.txt` exists with PyPI packages only (no `git+`, `-e`, `.whl`, `.tar.gz`)
5. No hardcoded secrets (check for `api_key = "..."` patterns excluding `os.getenv`/`os.environ`)

**Advisory (warnings):**

6. `fastmcp` listed in requirements.txt
7. `.gitignore` includes `.env`
8. No circular imports
9. Git repository initialised with remote
10. Server can load: `timeout 5 fastmcp inspect server.py`

### Step 6: Deploy

**FastMCP Cloud (simplest):**

```bash
git add . && git commit -m "Ready for deployment"
git push -u origin main
# Visit https://fastmcp.cloud, connect repo, add env vars, deploy
# URL: https://your-project.fastmcp.app/mcp
```

Cloud requirements:
- Module-level server object named `mcp`, `server`, or `app`
- PyPI dependencies only in `requirements.txt`
- Public GitHub repository
- Environment variables for secrets (no hardcoded values)
- Auto-deploys on push to main, PR preview deployments

**Docker (self-hosted):**

```dockerfile
FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["python", "server.py", "--transport", "http", "--port", "8000"]
```

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

---

## Critical Patterns

### Module-Level Server Instance

FastMCP Cloud requires the server instance at module level:

```python
# 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

# FIX for factory pattern -- export at module level
def create_server() -> FastMCP:
    mcp = FastMCP("server")
    return mcp
mcp = create_server()
```

### Type Annotations Required

FastMCP uses type annotations to generate tool schemas:

```python
@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:

```python
@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}"
```

### Cloud-Ready Server Pattern

```python
import os
from fastmcp import FastMCP

mcp = FastMCP("production-server")
API_KEY = os.getenv("API_KEY")

@mcp.tool()
async def production_tool(data: str) -> dict:
    if not API_KEY:
        return {"error": "API_KEY not configured"}
    return {"status": "success", "data": data}

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

---

## Common Errors and Fixes

These are the errors you will hit. Fix them before deploying.

| Error | Cause | Fix |
|-------|-------|-----|
| `RuntimeError: No server object found at module level` | Server inside a function | Export `mcp = FastMCP(...)` at module level |
| `RuntimeError: no running event loop` | Missing async/await | Use `async def` for async operations |
| `TypeError: missing required argument 'context'` | Context not type-hinted | Add `context: Context` with type hint |
| `ValueError: Invalid resource URI` | Missing URI scheme | Use `data://`, `file://`, `info://`, `api://` |
| Resource template parameter mismatch | Name mismatch | `user://{user_id}` needs `def get_user(user_id: str)` |
| Pydantic validation error | Wrong type hints | Ensure hints match actual data types |
| Transport mismatch | Client/server protocol differ | Match both to stdio or both to http |
| Import errors with editable package | Package not installed | `pip install -e .` or add to PYTHONPATH |
| `DeprecationWarning: mcp.settings` | Old API | Use `os.getenv()` instead |
| Port already in use | Stale process | `lsof -ti:8000 \| xargs kill -9` |
| Schema generation failure | Non-JSON types | Use JSON-compatible types (no NumPy arrays) |
| JSON serialization error | datetime/bytes in response | Convert to `.isoformat()` or string |
| Circular import | Factory in `__init__.py` | Use direct imports, avoid factory pattern |
| Python 3.12+ datetime warning | `datetime.utcnow()` deprecated | Use `datetime.now(timezone.utc)` |
| Import-time execution | Async resource at module level | Use lazy init pattern |

---

## Production Patterns

### Self-Contained Server

Keep all utilities in one file to avoid circular imports:

```python
from fastmcp import FastMCP
import os

mcp = FastMCP("my-server")

# Config
class Config:
    API_KEY = os.getenv("API_KEY", "")
    BASE_URL = os.getenv("BASE_URL", "https://ap