agentor and golf
About agentor
CelestoAI/agentor
Fastest way to build and deploy reliable AI agents, MCP tools and agent-to-agent. Deploy in a production ready serverless environment.
Provides a FastAPI-compatible MCP Server implementation (LiteMCP) with decorator-based tool definition and built-in authentication, plus a standardized Agent-to-Agent protocol using JSON-RPC messaging for multi-agent orchestration. Supports dynamic skill loading from Markdown files for context-aware task execution, and agents can be defined declaratively from Markdown with model/tool configuration.
About golf
golf-mcp/golf
Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents
Implements automatic component discovery via file-system conventions (tools, resources, prompts as Python modules) with Pydantic schema inference, eliminating manual server registration. Supports multiple transports (SSE, streamable-HTTP, stdio) and integrates OpenTelemetry for distributed tracing. Built-in auth layer handles JWT, OAuth Server, API keys, and dev tokens—all configured declaratively in `auth.py`.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work