---

name: mcp-forge description: "MCP (Model Context Protocol) server builder — guides creation of high-quality MCP servers in Python (FastMCP) or TypeScript (MCP SDK). Use when building integrations for AI agents." metadata: { "openclaw": { "emoji": "🔌", "homepage": "https://clawhub.ai/NakedoShadow", "requires": { "anyBins": ["node", "python", "python3", "uv"] }, "os": ["darwin", "linux", "win32"] } }

MCP Forge — Model Context Protocol Server Builder

Version: 1.1.0 | Author: Shadows Company | License: MIT

---

WHEN TO TRIGGER

• User wants to create an MCP server
• Integrating an external API/service with AI agents
• User says "build MCP", "create a tool server", "MCP server"
• Connecting a database, API, or service to Claude/OpenClaw

WHEN NOT TO TRIGGER

• Using existing MCP servers (just configure them)
• Building regular REST APIs (use standard web framework)

PREREQUISITES

Requires at least one of: python/python3/uv (for Python MCP servers) or node (for TypeScript MCP servers). The skill auto-detects the user's preferred stack based on available binaries.

• Python path: Requires fastmcp package (pip install fastmcp). Optional: httpx for HTTP clients, pytest for testing.
• TypeScript path: Requires @modelcontextprotocol/sdk and zod packages (npm install). Optional: tsx for development.
• uv path: Can replace pip/python with uv run for faster setup.

Additional tooling (pip, npm) is used only for dependency installation when explicitly requested by the user.

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QUICK DECISION: PYTHON OR TYPESCRIPT?

Factor	Python (FastMCP)	TypeScript (MCP SDK)
Speed to build	Faster (less boilerplate)	More setup
Type safety	Runtime checks	Compile-time checks
Ecosystem	Data/ML/scripting	Web/Node ecosystem
Hosting	uvx, pip	npx, npm

Default: Python with FastMCP unless the user needs TypeScript.

---

PYTHON — FastMCP Template

Minimal Server

from fastmcp import FastMCP

mcp = FastMCP("my-service", description="What this server does")

@mcp.tool()
async def my_tool(param: str) -> str:
    """Description of what this tool does.

    Args:
        param: Description of the parameter
    """
    # Implementation here
    return f"Result for {param}"

@mcp.resource("resource://{name}")
async def get_resource(name: str) -> str:
    """Fetch a named resource."""
    return f"Content of {name}"

Project Structure

my-mcp-server/
  __init__.py
  server.py          # FastMCP instance + tools
  config.py          # Environment variables, constants
  requirements.txt   # fastmcp, httpx, etc.
  README.md          # Usage instructions

Running

# Development
fastmcp dev server.py

# Install in Claude/OpenClaw
fastmcp install server.py --name "My Service"

# Or configure manually in settings

---

TYPESCRIPT — MCP SDK Template

Minimal Server

import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";

const server = new McpServer({
  name: "my-service",
  version: "1.0.0",
});

server.tool(
  "my-tool",
  "Description of what this tool does",
  { param: z.string().describe("Description of param") },
  async ({ param }) => ({
    content: [{ type: "text", text: `Result for ${param}` }],
  })
);

const transport = new StdioServerTransport();
await server.connect(transport);

Project Structure

my-mcp-server/
  src/
    index.ts        # McpServer instance + tools
    config.ts       # Environment variables
  package.json      # @modelcontextprotocol/sdk, zod
  tsconfig.json
  README.md

---

DESIGN PRINCIPLES

1. Tool Design

• One tool = one action — do not create god tools that handle multiple unrelated operations
• Clear names — get_user, create_issue, not do_thing
• Descriptive parameters — use docstrings/descriptions for every param
• Return structured data — JSON-serializable results
• Error handling — return error messages in the response, never let the server crash

2. Security

• Never hardcode secrets — use environment variables via os.environ or process.env
• Validate inputs — check types, ranges, formats at every tool boundary
• Sanitize outputs — strip internal paths, stack traces, and system details from responses
• Rate limiting — protect against runaway agent loops with request throttling
• Principle of least privilege — only request the permissions the tool actually needs

3. Performance

• Async by default — use async/await for all I/O operations
• Connection pooling — reuse HTTP clients and DB connections across tool calls
• Timeouts — set explicit timeouts (e.g., 30s) on all external calls
• Caching — cache frequently-accessed, rarely-changing data with TTL

4. Testing

# Python testing with FastMCP
import pytest
from fastmcp import Client

@pytest.fixture
def client():
    return Client(mcp)

@pytest.mark.asyncio
async def test_my_tool(client):
    result = await client.call_tool("my_tool", {"param": "test"})
    assert "Result" in result.text

---

CONFIGURATION FORMAT

For OpenClaw/Claude Desktop:

{
  "mcpServers": {
    "my-service": {
      "command": "python",
      "args": ["-m", "my_mcp_server.server"],
      "env": {
        "API_KEY": "from-env-or-secrets"
      }
    }
  }
}

---

SECURITY CONSIDERATIONS

This skill generates new source code files (scaffolding MCP servers). It does NOT execute the generated code during scaffolding.

• Commands suggested: pip install fastmcp, npm install @modelcontextprotocol/sdk — these install packages from public registries. Review package names before running.
• Data read: The skill reads the user's project structure to determine stack preferences. No sensitive files are accessed.
• Network access: None from the skill itself. Generated servers may make network calls depending on their purpose — this is by design and documented per-server.
• Credentials: The skill explicitly instructs to use environment variables for secrets and never hardcode credentials in source files.
• Persistence: Generated files are written to the working directory only. No global config changes.
• Sandboxing: Recommended to run generated MCP servers in isolated environments (containers, venvs) during development.

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RULES

1. One purpose per server — do not mix unrelated tools in a single server
2. Document every tool — description + parameter docs are mandatory for each tool
3. Environment variables for secrets — never hardcode API keys or tokens
4. Test before publishing — verify all tools work with a client before distribution
5. README is mandatory — every server must include installation, configuration, and usage examples

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Published by Shadows Company — "We work in the shadows to serve the Light."