Yuxi
Self-hosted, multi-tenant knowledge agent platform combining RAG, knowledge graphs, LangGraph multi-agent orchestration, MCP/Skills and sandboxed workspaces.
At a Glance
Yuxi core is released under the MIT License and can be self-hosted via Docker Compose at no cost. Third-party components pulled in by Docker Compose follow their own licenses; model API costs are external.
Engagement
Available On
Alternatives
Listed Nov 2026
About Yuxi
Yuxi is an open-source, self-deployable multi-tenant knowledge agent platform that its README summarizes as "Cloud Agents + Knowledge RAG". It brings knowledge-base retrieval, knowledge graphs, LangGraph multi-agent orchestration, MCP/Skills, sandbox tools and permission management into one workspace. It is released under the MIT License and started with Docker Compose.
What It Is
Yuxi targets teams that want to run an agent product on their own infrastructure while keeping control of data, models and permissions. Users chat with agents in a unified workbench, reference knowledge bases, personal files or Skills with @, and watch task steps, tool-call status and context token usage. Generated files can be previewed and downloaded.
Knowledge and RAG
Documents in formats such as PDF, Word, PPT, Excel and Markdown are parsed (MinerU, PaddleX and RapidOCR engines are listed), chunked and indexed as vectors in Milvus. Embedding and rerank models are configurable, with a retrieval test workbench and RAG evaluation using question-answer sets, including generated single-hop and multi-hop QA. Entities and relations can be extracted into Neo4j to build a knowledge graph, and a file-structure knowledge map can be browsed. External knowledge sources such as Dify and Notion can be connected.
Agents, Skills and Sandbox
An agent combines a model, prompts, knowledge bases, tools, MCP servers and SubAgents. A main agent can plan and dispatch SubAgents that run asynchronously in parallel. Skills can be installed online from skills.sh and ModelScope, edited, and given permissions and dependencies. Long-running tasks run through asynchronous workers, with human approval cards for sensitive actions. Sandboxed workspaces restrict file access and let agents produce Markdown, tables, HTML pages and code, previewed in the browser.
Team Governance and Setup
Administrators manage tenants, users, departments, sharing scope for knowledge bases, agents, Skills and models, plus API keys and a dashboard of requests, token use and queue status. Model providers include OpenAI, DeepSeek, Qwen, Zhipu, Moonshot, MiniMax, SiliconFlow, OpenRouter, ModelScope and OpenAI-compatible endpoints. Deployment uses Docker Compose with services including LangGraph, Vue, FastAPI, Milvus, Neo4j, PostgreSQL, MinerU and PaddleOCR; the docs describe an init script and a production deployment and upgrade guide.
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Pricing
Open Source (Self-hosted)
Yuxi core is released under the MIT License and can be self-hosted via Docker Compose at no cost. Third-party components pulled in by Docker Compose follow their own licenses; model API costs are external.
- MIT License
- Private/self-hosted deployment via Docker Compose
- Knowledge base RAG and knowledge graph
- Multi-agent orchestration with MCP/Skills/SubAgents
- Sandbox and permission management
Capabilities
Key Features
- Unified agent workbench with @-references to knowledge bases, files and Skills
- Knowledge base parsing, chunking, vector indexing, embedding and rerank
- Retrieval testing and RAG evaluation
- Knowledge graph construction with Neo4j and knowledge maps
- LangGraph multi-agent orchestration with parallel SubAgents
- Skills and MCP support with online Skill installation
- Sandboxed workspace with file generation and in-browser preview
- Human approval for sensitive actions
- Multi-tenant user, department and sharing permissions
- Model provider and API key management
- Dashboard for usage and runtime monitoring
- Docker Compose self-hosted deployment
