Lingyi Wanwu Connector for AI agents.
4 live capabilities
Connect your agent to high-performance bilingual Yi models for RAG and chat.
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Why people use Lingyi Wanwu
Lingyi Wanwu for Bilingual RAG and Chat
This Connector puts everything in one place for your agent. You can ask your agent to check your balance, list the latest models, and run a chat completion in a single flow. It gives you a direct line to 01.AI's infrastructure, letting you focus on building your product instead of managing the plumbing.
What Vinkius changes
You get a direct connection to 01.AI's models without the manual API setup.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Bilingual Customer Support
A developer needs a chatbot that handles both English and Chinese queries fluently.
- Real-world use case 02
Multilingual Knowledge Base
A knowledge engineer is building a RAG system.
- Real-world use case 03
Content Safety Gate
A dev wants to ensure user-generated content is safe.
Complete set · 4capabilities
The complete Lingyi Wanwu capability set.
These are the exact actions your AI can choose when you ask it to work with Lingyi Wanwu.
01—04
4 capabilities in this set.
Part of 4 available through Lingyi Wanwu.
- 01 Capability
Chat completions
Send a prompt to a Yi model to get a high-quality response. It works for both English and Chinese queries.
- 02 Capability
Check moderation
Scan your content for policy violations before you use it. This keeps your AI's output safe and compliant.
- 03 Capability
Get embeddings
Turn text into semantic vectors for your search capabilities. It's perfect for building out RAG pipelines.
- 04 Capability
List models
See which Yi models are currently available. This helps you pick the right balance of speed and intelligence for your specific task.
Set up in minutes
One URL. Then ask Lingyi Wanwu to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Lingyi Wanwu from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Lingyi Wanwu, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Lingyi Wanwu for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Lingyi Wanwu URL.
- Step 03
Save and start
Save the connection and enable Lingyi Wanwu in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"lingyi-wanwu": {
"url": "https://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Lingyi Wanwu
Open Agent mode in chat and ask: "Using Lingyi Wanwu, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"lingyi-wanwu": {
"url": "https://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Lingyi Wanwu
Ask Copilot: "Using Lingyi Wanwu, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"lingyi-wanwu": {
"url": "https://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Lingyi Wanwu
Open Cascade and ask: "Using Lingyi Wanwu, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"lingyi-wanwu": {
"url": "https://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Lingyi Wanwu
Ask Cline: "Using Lingyi Wanwu, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add lingyi-wanwu --transport http "https://edge.vinkius.com/vk_preview_JkyG9ZUTy0GPyUj394Vmol76jPwT4EVBKA0NvupX/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Lingyi Wanwu
Ask Claude: "Using Lingyi Wanwu, show me...". 4 tools are ready
Where the request belongs
Work Lingyi Wanwu can move forward.
This is for the developer who needs high-quality bilingual support and the knowledge engineer building RAG systems that need to understand more than just one language.
AI Developer
Integrating high-performance bilingual models into a custom app on a Tuesday afternoon.
Knowledge Engineer
Building a RAG pipeline that needs to turn 500 documents into semantic vectors for search.
System Integrator
Connecting an enterprise platform to the Yi foundation models for automated content checking.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Manage AI inference via Mistral. execute chat completions, generate RAG embeddings, and audit frontier models.
Together AI
Generate code, evaluate embeddings, and deploy open-source LLMs instantly from your local agent via Together AI's infrastructure.
Mistral AI
Build with European open-weight language models that deliver strong reasoning, multilingual capability, and efficient inference.
Gradient AI (LLM API & Finetuning)
Access powerful LLMs, fine-tune models on your own data, and generate embeddings directly through your AI agent.
DeepInfra (Serverless LLM Inference)
Run top-tier LLMs, image generation, and embeddings via DeepInfra's serverless infrastructure directly from your AI agent.
Bring your own AI
Change the model, client or framework. Keep Lingyi Wanwu connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Lingyi Wanwu.
The practical details behind the request, access and result.
What is the Lingyi Wanwu MCP?
It's a direct connection that lets your AI agent talk to 01.AI's Yi models. You can use it for chat, embeddings, and monitoring your account.
Can I use Lingyi Wanwu for Chinese language tasks?
Yes, it's specifically designed to handle high-quality bilingual tasks in both English and Chinese.
How does Lingyi Wanwu help with RAG?
It provides high-dimensional semantic embeddings. Your agent can turn your documents into vectors to power your search systems.
How do I monitor my costs with Lingyi Wanwu?
The Connector lets your agent check your current token balance and consumption. This helps you stay on budget while running your tasks.
Can the Lingyi Wanwu MCP check for unsafe content?
Yes, it includes a capability to scan your content for policy violations. This ensures your AI's output stays within your safety guidelines.
Is Lingyi Wanwu good for bilingual apps?
It's one of the best options for this. It's built to handle the nuances of both English and Chinese for chat and embeddings.
Which Yi model is best for complex reasoning?
For complex reasoning and high-quality outputs, yi-large is recommended. For faster response times and cost efficiency, yi-medium or yi-spark are excellent alternatives.
Can I automatically retrieve my remaining account balance?
Yes! Use the get_balance capability. Your agent will connect to the Lingyi Wanwu billing service and return your current remaining credits.
How do I list all the technical specs for the Yi models?
Use the list_models capability. Your agent will retrieve a list of all models currently available on the platform, along with their IDs and capabilities.
One connection away
Give your agent a direct line to Lingyi Wanwu.
Connect Lingyi Wanwu once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available