Golf MCP: Build Fast, Pythonic Agent Servers Without the Boilerplate

Golf is a no-frills, Python-first framework that turns a folder full of tools, prompts, and resources into a fully-functioning FastMCP server with built-in auth, observability, and a one-command build pipeline. If you can write an async def you can ship an MCP server before your morning espresso. We’ll install it, build a sample tool, wire it up to the OpenAI Agents SDK, and pit it against TypeScript-based MCP Framework and managed offerings like Composio MCP and PulseMCP.

1. What Exactly Is Golf?

Think of Golf as the “Rails-for-agents” layer that sits outside the MCP spec: it handles project scaffolding, routing, transport selection (SSE, Streamable HTTP, STDIO), auth, and telemetry so you only write the business logic.

On first run Golf scans your tools/, prompts/, and resources/ directories, auto-generates the MCP schemas, and spins up a FastAPI-based FastMCP server—no JSON schema hand-crafting, no YAML incantations.

Behind the scenes the CLI captures anonymous usage metrics (command name, success/failure) and sends them home unless you golf telemetry disable—a nice balance between product feedback and privacy.

2. Why Developers (and AI VPs) Care

3. Five-Minute Quick Start

“Let’s get a server running before this paragraph ends.”

# 1. Install the CLI
pip install golf-mcp        # Python 3.10+

# 2. Scaffold
golf init hello-golf
cd hello-golf

# 3. Run in dev mode
golf build dev
golf run           # => http://127.0.0.1:3000

Golf drops a project tree like:

hello-golf/
├─ golf.json
├─ tools/
│  └─ hello.py
├─ prompts/
├─ resources/
└─ .env

Writing Your First Tool

# tools/hello.py
"""Greet a user."""

from typing import Annotated
from pydantic import BaseModel, Field

class Output(BaseModel):
    message: str

async def hello(
    name: Annotated[str, Field(description="Who to greet")] = "World",
    greeting: Annotated[str, Field(description="Greeting phrase")] = "Hello",
) -> Output:
    print(f"{greeting}, {name}!")
    return Output(message=f"{greeting}, {name}!")

export = hello   # Golf’s discovery flag

Restart the dev server and the tool is instantly live under the MCP ID hello.

4. Deep-Dive Features You’ll Actually Use

4.1 Observability

Flip a switch in golf.json:

{
  "opentelemetry_enabled": true,
  "opentelemetry_default_exporter": "otlp_http"
}

…and Golf traces every tool invocation, prompt render, and HTTP hop. Swap Jaeger or Tempo endpoints via OTEL_EXPORTER_OTLP_ENDPOINT.

4.2 Transport Flexibility

• SSE – great for web clients
• Streamable HTTP – follows the 2025-03-26 MCP spec for chunked responses
• STDIO – spawn your server as a subprocess for local IDE integrations

4.3 Road-map Goodies

golf deploy promises one-command pushes to Vercel & friends, plus encrypted OAuth token storage for long-running agents. VP-level peace of mind.

5. From Local to Agent: Golf × OpenAI Agents SDK

from openai_agents_python.mcp import MCPServerSse
from agents import Agent

# 1. Point the SDK to your Golf server
golf_server = MCPServerSse(url="http://127.0.0.1:3000", cache_tools_list=True)

# 2. Wire into an agent
agent = Agent(
    name="Assistant",
    instructions="Use the MCP tools to get stuff done",
    mcp_servers=[golf_server],
)

response = await agent.run("Say hello to the CFO")
print(response)

The SDK auto-lists Golf’s tools and lets the LLM call them with zero extra glue.

6. How Does Golf Stack Up?

6.1 Golf vs MCP Framework (TypeScript)

6.2 Golf vs Composio MCP (Managed SaaS)

6.3 Golf vs PulseMCP / Registries

• PulseMCP & peers (Smithery, MCP.so) are discovery layers—think “npm for MCP servers.” They complement, not replace, Golf.
• You can publish your Golf server to any registry once golf deploy lands.

7. Production Checklist

1. Containerize: Drop your build into a slim Python 3.12-alpine image; follow the Snyk hardening tips for MCP servers-in-Docker.
2. Rate-limit: Front your server with an API gateway; Golf’s upcoming deployment helper will expose per-tenant throttles.
3. Observability budget: Export OTLP traces to Grafana Tempo; log volumes add up quickly.
4. Token hygiene: If you roll your own OAuth, encrypt at rest—don’t wait for the roadmap.

8. Best Practices & Pro Tips

• Module docstrings == tool descriptions – keep them crisp; they surface directly in agent UIs.
• Group domain logic under sub-folders (tools/payments/charge.py)—Golf turns path segments into hyphen-delimited IDs, preventing name collisions.
• Cache tool lists on the client (cache_tools_list=True) to shave latency in chat loops.
• Humor-driven logging: sprinkle a witty log message—debugging at 2 a.m. needs comic relief.

9. Conclusion – Should You Swing With Golf?

If your stack is Python, you want full control, and you value time-to-MCP over having 250 ready-made SaaS integrations, Golf is a hole-in-one. For TypeScript shops, MCP Framework feels more native. Need off-the-shelf Gmail, Sheets, and HubSpot? Composio MCP is turnkey. The beauty of MCP’s plug-and-play ethos is that you can mix-and-match: prototype in Golf, then bolt on Composio servers as business needs grow.

Whichever fairway you choose, may your tests be green and your logs free of sand-trap stack traces.

Tega AdeyemiMay 26, 2025