Open-Source Observability · golf-mcp

golf

Golf is a Python framework for building MCP (Model Context Protocol) servers with minimal boilerplate. It provides built-in authentication, observability, and telemetry for deploying AI agent infrastructure.

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Source: GitHub — github.com/golf-mcp/golf

834

GitHub stars

Forks

Python

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	golf-mcp/golf
Owner	golf-mcp
Primary language	Python
License	Apache-2.0 — OSI-approved
Stars	834
Forks	69
Open issues	0
Latest release	v0.3.0 (2026-05-08)
Last updated	2026-05-08
Source	https://github.com/golf-mcp/golf

What golf is

Golf automates MCP server scaffolding by discovering Python components (tools, prompts, resources) in conventional directories and compiling them into a runnable server. It includes JWT/OAuth/API-key authentication, OpenTelemetry integration, and CLI tooling (build, run, init).

Quickstart

Get the golf source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/golf-mcp/golf.git2cd golf3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Rapid MCP Server Prototyping

Build production-ready MCP servers in minutes with minimal configuration. Ideal for teams moving quickly from concept to deployed agent infrastructure.

Enterprise AI Agent Backends

Deploy secure, observable AI agent services with enterprise authentication (JWT, OAuth) and automatic telemetry collection built in.

Multi-Tool Agent Systems

Organize complex agent capabilities (tools, prompts, resources) in a modular, discoverable structure without writing boilerplate server code.

Implementation considerations

Python 3.10+ required; test dependency compatibility before deployment.
Authentication configuration (auth.py) is mandatory and must be chosen upfront (JWT, OAuth, API key, or dev tokens); no authentication-free mode.
Component discovery relies on strict directory structure (tools/, resources/, prompts/); deviations break automatic registration.
OpenTelemetry integration is optional but recommended for production; requires external OTLP endpoint if enabled.
Module docstrings and Pydantic models are used for introspection; incorrect schema definitions will cause registration failures.

When to avoid it — and what to weigh

Non-Python AI Infrastructure — Golf is Python-only. If your team uses Node.js, Go, or other runtimes, you will need an alternative MCP framework.
Simple Standalone Tools — Overhead of a framework is not justified for single-endpoint tools. Direct MCP server implementation may be faster for trivial use cases.
Strict Legacy System Integration — Requires conventional directory structure and Pydantic models. Existing systems with incompatible architectures may need refactoring.
Proven Maturity Required — Project created Feb 2025 with latest release May 2026. Early-stage framework; production adoption still ramping. Evaluate risk tolerance for critical workloads.

License & commercial use

Apache License 2.0 (Apache-2.0). Permissive OSI-approved open-source license. Allows commercial use, modification, and distribution with attribution and indemnification clauses.

Apache-2.0 is a permissive OSI license that permits commercial use without restriction. No license cost or proprietary limitations. Include a copy of the license and original notice in distributed software. Review indemnification and warranty disclaimers (AS-IS) before deploying in mission-critical environments.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Strong
Assessment confidence	High

Security considerations

Framework provides authentication mechanisms (JWT, OAuth Server, API key, dev tokens) and supports OpenTelemetry observability. No security audit or certification mentioned. Auth configuration is developer's responsibility; misconfiguration (e.g., missing JWKS validation, weak tokens in dev mode) can expose agents. Telemetry can include input/output if detailed_tracing enabled; use with caution on sensitive data. Verify OWASP practices (injection, auth bypass, data leakage) through code review before production deployment.

Alternatives to consider

Anthropic MCP Reference Implementation

Official MCP server spec; language-agnostic, but lower-level; requires more boilerplate. Choose if you need maximum flexibility or non-Python runtime.

Zapier AI Actions / LangChain Agent Toolkit

Lower overhead for simple tool registration; broader ecosystem integrations. Choose if you prioritize third-party SaaS connectors over custom MCP infrastructure.

Manual but transparent implementation; full control over auth, telemetry, and deployment. Choose if you prefer minimal abstraction or have unusual architectural constraints.

Software development agency

Build on golf with DEV.co software developers

Start with `pip install golf-mcp` and `golf init your-project-name`. Have questions about architecture, authentication, or deployment? Let's discuss your AI infrastructure needs.

Talk to DEV.co

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golf FAQ

Can I use Golf with non-Python code?

No. Golf is Python-only. You can call external binaries or APIs from Python tools, but the server framework and tool definitions must be Python.

Is authentication optional?

No. You must configure an auth method in auth.py (JWT, OAuth Server, API key, or dev tokens). There is no authentication-free mode.

Does Golf handle deployment (Docker, Kubernetes, etc.)?

Not explicitly. Golf provides CLI commands to run locally. Deployment (containerization, scaling, orchestration) is your responsibility. See golf.json transport and port config for runtime options.

What is the telemetry policy?

Anonymous usage data is collected by default (commands, success/failure, versions, OS). No code, project names, or error messages. Opt out via 'golf telemetry disable' or --no-telemetry flag.

Work with a software development agency

From first prototype to production, DEV.co delivers software development services around tools like golf. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across open-source observability and beyond.

Ready to Build Your MCP Server?

Start with `pip install golf-mcp` and `golf init your-project-name`. Have questions about architecture, authentication, or deployment? Let's discuss your AI infrastructure needs.

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