Overview / Description
Agora is an open-source AI multi-agent tool that splits a task across specialized roles so a team of agents can research, debate, and execute it for developers and technical teams. Instead of a single chatbot, Agora runs a council of agents with distinct jobs: a moderator routes the request, a scout gathers information, an architect designs the solution, a critic reviews risks, a synthesizer turns the discussion into action items, and an executor carries out approved steps. It supports routing modes such as QUICK, DISCUSS, EXECUTE, and CLARIFY, and includes built-in tools for file reading and writing, directory listing, and shell execution, all behind human-in-the-loop approval before anything runs. Agora is model-agnostic and connects to OpenAI, Azure OpenAI, Claude, Gemini, and other compatible APIs, with agent and prompt behavior configured through editable YAML files. It ships with a web UI and a REST API (an /api/chat endpoint), can be self-hosted via Docker, and includes a self-learning step that distills past discussions and executions into reusable skills. Released under the MIT license, this multi-agent system is aimed at people who want transparent, multi-perspective reasoning and artifact generation in one interface rather than a black-box single agent.
Used For
Best for developers and technical teams who want a self-hosted, multi-agent AI system that researches, debates, and executes tasks with human approval rather than relying on a single black-box assistant.
Pricing
Open Source (MIT)
Free and open-source under the MIT license; you supply your own model API keys and host it yourself.
Pros & Cons
Pros
- Role-based agents (scout, architect, critic, synthesizer, executor) give multi-perspective reasoning instead of one black-box response
- Model-agnostic: works with OpenAI, Azure OpenAI, Claude, Gemini, and other compatible APIs
- Human-in-the-loop approval gates execution of file and shell operations
- Self-hostable via Docker with both a web UI and a REST API
- Agent and prompt behavior is customizable through editable YAML config
Cons
- Requires self-hosting and your own model API keys, so there is setup and infrastructure overhead
- As open-source software it ships without managed support or SLAs
- Multi-agent debate across several roles can increase token usage and latency versus a single agent
Questions & Answers
Alternatives
AutoGen, CrewAI, LangGraph, MetaGPT