Nexent is a zero-code platform for auto-generating agents — no orchestration, no complex drag-and-drop required, using pure language to develop any agent you want. Built on the MCP ecosystem with rich tool integration, Nexent also provides various built-in agents to meet your intelligent service needs in different scenarios such as work, travel, and daily life. Nexent offers powerful capabilities for agent running control, multi-agent collaboration, data processing and knowledge tracing, multimodal dialogue, and batch scaling.
One prompt. Endless reach.
- 🌐 Visit our official website to learn more
- 🚀 Try it now to experience the power of Nexent
Nexent.Intro.mp4
If you want to go fast, go alone; if you want to go far, go together.
We have released Nexent v1, and the platform is now relatively stable. However, there may still be some bugs, and we are continuously improving and adding new features. Stay tuned: we will announce v2.0 soon!
- 🗺️ Check our Feature Map to explore current and upcoming features.
- 🔍 Try the current build and leave ideas or bugs in the Issues tab.
Rome wasn't built in a day.
If our vision speaks to you, jump in via the Contribution Guide and shape Nexent with us.
Early contributors won't go unnoticed: from special badges and swag to other tangible rewards, we're committed to thanking the pioneers who help bring Nexent to life.
Most of all, we need visibility. Star ⭐ and watch the repo, share it with friends, and help more developers discover Nexent — your click brings new hands to the project and keeps the momentum growing.
| Resource | Minimum |
|---|---|
| CPU | 2 cores |
| RAM | 6 GiB |
| Software | Docker & Docker Compose installed |
git clone https://github.com/ModelEngine-Group/nexent.git
cd nexent/docker
cp .env.example .env # fill only nessasary configs
bash deploy.shWhen the containers are running, open http://localhost:3000 in your browser and follow the setup wizard.
Check our MCP Ecosystem page for detailed information about the MCP tool ecosystem, including community hubs, recommended tools, and integration guides.
Check our Agent Scenarios page for detailed agent use cases and best practices, including travel planning, research assistant, business intelligence, smart lifestyle, and more scenarios.
1 Smart agent prompt generation
Turn plain language into runnable prompts. Nexent automatically chooses the right tools and plans the best action path for every request.
2 Scalable data process engine
Process 20+ data formats with fast OCR and table structure extraction, scaling smoothly from a single process to large-batch pipelines.
3 Personal-grade knowledge base
Import files in real time, auto-summarise them, and let agents access both personal and global knowledge instantly, also knowing what it can get from each knowledge base.
4 Internet knowledge search
Connect to 5+ web search providers so agents can mix fresh internet facts with your private data.
5 Knowledge-level traceability
Serve answers with precise citations from web and knowledge-base sources, making every fact verifiable.
6 Multimodal understanding & dialogue
Speak, type, files, or show images. Nexent understands voice, text, and pictures, and can even generate new images on demand.
7 MCP tool ecosystem
Drop in or build Python plug-ins that follow the MCP spec; swap models, tools, and chains without touching core code.
Check our Model Providers page for detailed model configuration guides and recommended provider information.
Want to build from source or add new features? Check the Contribution Guide for step-by-step instructions.
Prefer to run Nexent from source code? Follow our Developer Guide for detailed setup instructions and customization options.
Check our Known Issues page for the latest issue status and solutions.
- Browse the FAQ for common install issues.
- Join our Discord community to chat with other developers and get help!
- File bugs or feature ideas in GitHub Issues.
Nexent is licensed under the MIT with additional conditions. Please read the LICENSE file for details.