coze-studio
An AI agent development platform with all-in-one visual tools, simplifying agent creation, debugging, and deployment like never before. Coze your way to AI Agent creation.
Open-source visual platform for building, debugging, and deploying AI agents and workflows without coding. Includes no-code tools, knowledge bases, plugins, and integrations.
Coze Studio is an open source platform for building AI agents — programs that combine a large language model with tools, data, and instructions to carry out work on a user's behalf. It is the open source core of the commercial Coze Development Platform, which the team says has served tens of thousands of enterprises and millions of developers. The pitch is visual development. Instead of writing an agent from scratch in code, you use a no-code or low-code interface to design it, hook it up to the resources it needs (a chosen language model, a knowledge base, plugins, a database, a prompt), test and debug it, then publish it as a chat experience or expose it through APIs and a Chat SDK. The Feature List names the main building blocks: model management with built-in support for services such as OpenAI and Volcengine, an agent builder, an app builder, a workflow editor, a resource manager for plugins, knowledge bases, databases and prompts, and an OpenAPI plus Chat SDK for embedding agents into your own product. To run it yourself, the README walks through cloning the repo and starting it via Docker Compose; once up, you reach the web UI on localhost port 8888. The recommended minimum is 2 CPU cores and 4 GB of RAM. The README also flags security considerations for public deployments — account registration, the Python execution environment in workflow code nodes, SSRF, and privilege escalation paths in APIs are called out as risks to assess before going public. The backend is written in Go (1.23.4 or later), the frontend in React with TypeScript, and the system is built as microservices following domain-driven design principles. Released under the Apache 2.0 license.
Where it fits
- Build a customer support chatbot with knowledge bases and integrate it into your website using the Chat SDK.
- Create an internal workflow automation tool that connects to your databases and external APIs without writing backend code.
- Deploy a multi-step AI agent that uses plugins to fetch data, process it, and trigger actions in your business systems.
- Develop and test AI agent logic visually before publishing to production or sharing with enterprise customers.