Open WebUI Connector for AI agents.
12 live capabilities
Manage your local LLM infrastructure and RAG collections from your chat.
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Why people use Open WebUI
Open WebUI for Automated RAG Data Ingestion
With this Connector, you just give your agent the URL or the file. It handles the upload, the processing, and the collection placement. You can even ask it to check if the file is ready to use. It turns a multi-step manual chore into a single conversational command.
What Vinkius changes
You get a direct remote control for your Open WebUI instance from inside your AI chat.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Building a private knowledge base
A researcher wants to ingest 50 PDFs.
- Real-world use case 02
Rapid model testing
A developer wants to see which model handles a specific task best.
- Real-world use case 03
Automated web scraping
A content manager wants to feed a blog post into their RAG.
Complete set · 12capabilities
The complete Open WebUI capability set.
These are the exact actions your AI can choose when you ask it to work with Open WebUI.
01—04
4 capabilities in this set.
Part of 12 available through Open WebUI.
- 01 Capability
Add file to collection
Put a specific file into a knowledge collection. This helps keep your data organized by topic.
- 02 Capability
Chat completed
Run outlet filters for a finished conversation. It helps with post-chat processing and logging.
- 03 Capability
Ollama generate
Get a completion directly from Ollama. This is the fastest way to run local inference.
- 04 Capability
Ollama tags
List all the tags and models in your Ollama setup. It helps you keep track of your local library.
05—08
4 capabilities in this set.
Part of 12 available through Open WebUI.
- 05 Capability
Process web url
Turn a website link into a knowledge collection. This is the quickest way to add web data to your system.
- 06 Capability
Chat completions
Get a response using an OpenAI-compatible endpoint. This works well for standard chat tasks.
- 07 Capability
Create new chat
Start a new conversation with a backend-controlled flow. It ensures every new chat gets a unique ID.
- 08 Capability
Get file status
Check if your document is finished processing. This is useful for knowing when your data is ready.
09—12
4 capabilities in this set.
Part of 12 available through Open WebUI.
- 09 Capability
List models
See every model available in your instance. It lets you quickly identify which models are ready to use.
- 10 Capability
Ollama embed
Generate embeddings using the Ollama API. Use this for creating vector representations of your data.
- 11 Capability
Send message
Generate a response using an Anthropic-compatible endpoint. It's great for specific message-based workflows.
- 12 Capability
Upload file
Send a file to your vector database for RAG. This is how you get your local documents into the system.
Set up in minutes
One URL. Then ask Open WebUI to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Open WebUI 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_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Open WebUI for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI URL.
- Step 03
Save and start
Save the connection and enable Open WebUI in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"open-webui": {
"url": "https://edge.vinkius.com/vk_preview_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI
Open Agent mode in chat and ask: "Using Open WebUI, help me...". 12 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"open-webui": {
"url": "https://edge.vinkius.com/vk_preview_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI
Ask Copilot: "Using Open WebUI, help me...". 12 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"open-webui": {
"url": "https://edge.vinkius.com/vk_preview_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI
Open Cascade and ask: "Using Open WebUI, help me...". 12 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"open-webui": {
"url": "https://edge.vinkius.com/vk_preview_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI
Ask Cline: "Using Open WebUI, help me...". 12 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add open-webui --transport http "https://edge.vinkius.com/vk_preview_YhwRL8adKsCUXpVOwybG0l7vG8Iky4FGyj9DhmOn/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 Open WebUI
Ask Claude: "Using Open WebUI, show me...". 12 tools are ready
Where the request belongs
Work Open WebUI can move forward.
This is for the person who feels buried in tabs trying to manage local LLMs and knowledge base data. It's for the engineer who needs to toggle models and check file statuses without hunting for a URL.
AI Engineer
Automates model testing and RAG configuration checks without leaving the terminal.
Knowledge Manager
Rapidly ingests documentation and web URLs into organized collections via simple commands.
DevOps Engineer
Monitors local Ollama instances and manages model availability across the organization.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsFlowiseAI
Build LLM orchestration flows visually with a drag-and-drop interface for creating AI chatbots, agents, and RAG pipelines.
Dify
Manage agentic workflows via Dify. send chat messages, track conversations, audit app parameters, and handle file uploads directly from any AI agent.
VectorShift (AI Workflow & RAG Automation)
Automate AI workflows and RAG via VectorShift. manage pipelines, query knowledge bases, and deploy chatbots directly from any AI agent.
Portkey
AI gateway observability: monitor logs, costs, and manage LLM configurations via agents.
Eden AI
Equip your AI agent to manage unified AI workflows, track providers, and monitor API usage via the Eden AI platform.
Mistral AI (Frontier LLMs & Embeddings)
Manage AI inference via Mistral. execute chat completions, generate RAG embeddings, and audit frontier models.
Bring your own AI
Change the model, client or framework. Keep Open WebUI connected.
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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 Open WebUI.
The practical details behind the request, access and result.
Can I use the Open WebUI MCP to manage my local models?
Yes. This Connector connects to your Open WebUI instance, allowing your AI agent to list, tag, and generate completions for models running locally via Ollama or other providers.
How do I add documents to my RAG system using this?
You can simply ask your agent to upload a file or provide a web URL. The Connector handles the extraction and adds the content to your specified knowledge collections automatically.
Does the Open WebUI MCP work with Claude or Cursor?
Yes, it works with any MCP-compatible client. You just need to provide your Open WebUI Base URL and API key in the connection settings.
Can I check if my files are finished processing?
Yes. You can ask your agent to check the status of a specific file, and it will tell you if the document is ready to be used as RAG context.
Is it possible to create new chats automatically?
Yes. The Connector includes a capability to create new chats that handles the backend-controlled flow and ensures every new session gets its own unique ID.
Can I use this to manage multiple different AI models?
Yes. It can fetch and list all models available in your instance, including those from Ollama, OpenAI, and custom Open WebUI functions.
How can I check if a model is available in my Open WebUI instance?
You can use the list_models capability. It will return a complete list of all configured models, including those from Ollama, OpenAI, and internal Open WebUI functions.
Can I add a website to my RAG collection using just a URL?
Yes! Use the process_web_url capability. Provide the URL and the target collection name, and the server will scrape and index the content for you.
How do I know when my uploaded file is ready for querying?
After using upload_file, you can check the ingestion progress by calling get_file_status with the returned File ID. It will tell you if the status is 'completed' or 'pending'.
One connection away
Give your agent a direct line to Open WebUI.
Connect Open WebUI once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available