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Build, test, and evaluate AI agents with strong model and MCP support.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "fast-agent" yet — see the docs or source repo.
Using fast-agent, generate a customer support agent project scaffold with model configuration, tool integration, conversation flow, and local run instructions.
A runnable agent project structure with key config files and setup instructions.
Use fast-agent to design an evaluation plan for my sales assistant agent, including test cases, scoring metrics, automated evaluation flow, and result interpretation guidance.
An actionable evaluation framework to compare response quality and reliability.
Based on fast-agent, show how to connect multiple MCP tools to one agent, with example configuration, invocation patterns, and debugging tips.
A multi-tool integration example covering setup, invocation flow, and common debugging approaches.
Discover, browse, and install agent skills from curated GitHub sources.
Expose Agent Skills as MCP tools for coding agents to discover and activate instructions.
Build and manage MCP servers and clients quickly with Python.
Provides 17 tools to evaluate, improve, and build LLM agents.
Learn provider-neutral agent design best practices across coding agent environments.
Build, run, inspect, and analyze CFAST fire models step by step.