evalstate/fast-agent

Health v2 · maintenance only

Adoption not part of the score

3931 stars · 447 forks observed · 2026-10-13

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

fast-agent is a Python CLI-first framework for building, running, and evaluating LLM agents with first-class MCP, ACP, and A2A protocol support. It provides an interactive terminal UI with shell integration, skills/plugins, workflow orchestration, and broad provider support including local llama.cpp models.

Use cases

• build and evaluate llm agents from the terminal
• coding agent with shell and subagent support
• connect and test mcp servers with sampling and elicitation
• expose an agent as an a2a or acp endpoint
• run local llama.cpp models with an agent harness
• evaluate model accuracy and cost across providers
• manage agent skills and plugins

When to choose

• you want a terminal-native, scriptable agent harness with strong MCP support
• you need ACP/A2A client and server interoperability
• you want broad provider coverage including local models and Codex subscriptions
• you need agent evaluation and workflow tooling in Python

When to avoid

• you need a hosted GUI or web-based agent builder
• you only want a simple chatbot SDK without protocol integrations
• you require a non-Python runtime

Facets

framework · maturity active

agent-framework llm-inference cli mcp chatbot developer-tools terminal-ui plugin-system large-language-models developer-tools python cli cross-platform windows mcp-client mcp-server acp a2a agent-skills coding-agent tui llm-evaluation card-packs ai-agents command-line automation macos linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="evalstate/fast-agent")