Open Source Multi-Agent Frameworks for Developers
Why open source matters for multi-agent AI systems — transparency, community contribution, self-hosting, and the state of open source agent frameworks in 2026.
Most AI coding tools are closed-source services. You send code to a remote API, get results back, and have limited visibility into how decisions are made. Open source multi-agent frameworks offer an alternative: full transparency, local execution, and community-driven development.
Why open source for agent systems
- Transparency — inspect agent logic, prompts, and orchestration code
- Self-hosting — run agents on your own infrastructure with your own models
- Customization — modify agent behavior, add new agent types, adjust workflows
- Community — contribute improvements, report issues, and share patterns
- No vendor lock-in — switch models, providers, or deployment targets freely
DeepRise as an open source option
DeepRise is an open-source multi-agent system released under the MIT license. It provides a full agent swarm — super agent, orchestration, development, testing, review, security, and DevOps agents — that developers can run locally or in their own CI environment.
The project is actively developed on GitHub. Contributors can add new agent types, improve orchestration logic, or extend the SDK. Installation is a single command, and the codebase is structured as a monorepo with packages for the core runtime, SDK, and infrastructure.
Contributing
If you are interested in multi-agent systems and want to contribute to open source AI tooling, DeepRise welcomes contributions on GitHub. Whether it is a new agent type, improved test coverage, or documentation — the project benefits from community involvement.