{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/8"}],"enrichment":{"capability":"fast-agent-mcp is a CLI-first framework for building and running LLM agents with Model Context Protocol (MCP) server integration, supporting multiple LLM providers and interactive or programmatic execution.","skillfed_tags":["llm-agents","mcp-framework","multi-provider"],"use_cases":["Build a coding agent that uses MCP servers for file system access, LSP integration, and tool execution to assist with development tasks.","Create a multi-step workflow where agents chain together (e.g., researcher \u2192 evaluator \u2192 optimizer) using shared MCP servers for data access.","Set up an interactive CLI tool that lets users chat with an LLM agent backed by custom MCP servers for domain-specific tasks.","Develop and test agent applications locally with model passthrough and playback LLMs before deploying to production.","Expose an agent as an MCP server itself for use in other applications via stdio or HTTP transport with OAuth authentication."],"what_it_does":"fast-agent-mcp is a framework for building and orchestrating LLM agents that interact with Model Context Protocol (MCP) servers. It provides both a CLI interface and a Python API, supporting agents as simple decorators or complex workflows. The framework handles agent skill management, MCP server connections, and multi-model provider support (Anthropic, OpenAI, Google, Azure, Ollama, and others via TensorZero), with built-in features for structured outputs, vision, PDF handling, and shell integration.\n\nThe package is designed for rapid agent development with minimal boilerplate. Agents can be run interactively via a prompt-toolkit-powered terminal interface with streaming responses via rich, or programmatically in automation and server modes. It includes diagnostic tools for MCP transport inspection, OAuth-based secret management via keyring, and support for agent chaining and workflow composition. The framework emphasizes declarative configuration through YAML files and simple Python decorators, enabling developers to focus on prompt and MCP server composition rather than infrastructure.","worth_installing":"Yes, if you are building LLM agents with MCP server integration. The framework is actively maintained, has low install friction, permissive licensing, and no known vulnerabilities. The large dependency footprint is justified by multi-provider support and feature completeness. Install only if you need agent orchestration; it is not suitable for simple LLM API calls."},"id":"fast-agent-mcp","links":{"html":"https://skillfed.io/packages/fast-agent-mcp","md":"https://skillfed.io/packages/fast-agent-mcp.md","pypi":"https://pypi.org/project/fast-agent-mcp/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-13","license_spdx":null,"license_treatment":"permissive","name":"fast-agent-mcp","python_support":"supports_current","summary":"Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support"},"popularity":{"monthly_downloads":157584,"position":10750,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.10.7"}