fast-agent vs pydantic-ai-harness
Python agent frameworks compared
fast-agent is a Python framework and CLI for building, running, and evaluating LLM agents, including multi-agent workflows and MCP connections. pydantic-ai-harness adds composable capabilities to Pydantic AI agents, with a focus on coding, research, memory, and long-running work; its repository is no longer updated.
fast-agent: Build and Run LLM Agents and Workflows
A Python framework and CLI for building, testing, and running LLM agents that use MCP tools and compose into workflows. It suits developers who want both interactive agent development and a programmable framework.
pydantic-ai-harness: Add Capabilities to Pydantic AI Agents
Pydantic AI Harness is a Python capability library built on Pydantic AI for giving agents workspaces, memory, delegation, and other tools for complex, long-running tasks. This GitHub repository is archived; development and documentation have moved to the Pydantic AI repository.
| fast-agent | pydantic-ai-harness | |
|---|---|---|
| Language | Python | Python |
| License | Apache-2.0 | MIT |
| Stars | 3.9k | 958 |
| Forks | 446 | 150 |
| Last analyzed | Oct 7, 2026 | Oct 19, 2026 |
Key differences
- fast-agent provides a framework and CLI, while pydantic-ai-harness extends agents built with Pydantic AI.
- fast-agent emphasizes agent workflows, model-provider options, MCP connections, and interactive terminal use; pydantic-ai-harness emphasizes capabilities such as coding tools, persistent memory, delegation, and context management.
- fast-agent supports native Anthropic, OpenAI, and Google providers, plus other providers through TensorZero; pydantic-ai-harness is designed for Pydantic AI agents.
- fast-agent is licensed under Apache-2.0, while pydantic-ai-harness is licensed under MIT.
- fast-agent is not archived; pydantic-ai-harness is no longer updated, with ongoing development and support moved to the Pydantic AI repository.
- fast-agent is suited to developers composing and running agent applications; pydantic-ai-harness suits developers extending Pydantic AI agents for complex or long-running tasks.
Choose fast-agent if you…
- need a Python framework and CLI for building and running LLM agents.
- want to compose multi-agent workflows or connect agents to MCP servers.
- prefer interactive terminal use and options for running agents through MCP servers or ACP clients.
Choose pydantic-ai-harness if you…
- want to add coding, research, memory, or delegation capabilities to a Pydantic AI agent.
- need context management and support for durable or resumable agent runs.
- are working with the preserved v0.36.0 history and can use the Pydantic AI repository for current releases and support.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.