About deer-flow
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
What you should know about deer-flow
deer-flow — An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.. It is categorized under AI Tools and primarily built with Python. The project has gathered 61,866 stars and 7,978 forks on GitHub, indicating strong adoption among developers.
Pricing & licensing: This tool is offered free of charge , released under the MIT license. The source code is openly available on GitHub, allowing engineers to audit, contribute, or fork as needed.
Use cases & topics: deer-flow is associated with the following topics: agent, agentic, agentic-framework, agentic-workflow, ai, ai-agents, deep-research, harness. Teams working in agent / agentic / agentic-framework spaces typically evaluate this kind of tool when scoping new architecture decisions or replacing legacy components.
Getting started: Check out the official GitHub repository for installation steps, configuration examples, and the latest release notes. Most teams hit value within the first week if the tool aligns with their existing AI Tools stack.
Editor's note from Fanny Engriana (Founder, Wardigi Digital Agency): when evaluating tools in the AI Tools category for our agency clients, we look at three things first — license clarity, community size, and active maintenance. Tools with explicit license terms and ongoing commits tend to remain viable across multi-year projects.