> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mcpblacksmith.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Local Development

> Run your generated MCP server locally for development and testing.

## Running the server

After installing dependencies and configuring `.env`:

```bash theme={null}
python server.py
```

By default, the server starts with **stdio** transport — the standard for local MCP connections.

## Transport options

Select a transport at runtime:

```bash theme={null}
# stdio (default) — for direct MCP client connections
python server.py

# SSE — for network-based connections
python server.py --transport sse --port 8000

# Streamable HTTP — newer HTTP-based transport
python server.py --transport streamable-http --port 8000
```

| Transport           | Use case                                                |
| ------------------- | ------------------------------------------------------- |
| **stdio**           | Local MCP clients (Claude Desktop, Claude Code, Cursor) |
| **SSE**             | Remote or Docker-based deployments                      |
| **streamable-http** | Newer MCP clients that support HTTP streaming           |

## Virtual environment

It's recommended to use a virtual environment:

```bash theme={null}
cd my-api-server
python -m venv .venv
source .venv/bin/activate    # Linux/macOS
# .venv\Scripts\activate     # Windows
pip install -r requirements.txt
python server.py
```

## Testing tools manually

Run the server and connect an MCP client to test individual tools. Try asking the AI agent to perform operations:

> "List all users"
> "Create a new order for product X"
> "Get the status of order #123"

Check the server's terminal output for request logs, errors, and validation warnings.