LibreChat Connector for AI agents.
4 live capabilities
Connect your private LLM environment to your favorite AI capabilities.
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Why people use LibreChat
LibreChat for self-hosted LLM orchestration
This Connector changes that by making your LibreChat instance a first-class citizen in your AI toolkit. Instead of jumping between windows, your agent handles the connection for you. You get a unified experience where your private models are just another capability your agent can reach out and use whenever you need them.
What Vinkius changes
You get a direct bridge from your local LLM setup to your favorite AI capabilities without manual switching.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Testing local models in your IDE
An AI engineer wants to see how a locally hosted model handles code refactoring.
- Real-world use case 02
Automated structured data extraction
A researcher needs to pull data from a private agent.
- Real-world use case 03
Centralizing private agent access
A power user wants to use their 'Research' and 'Writing' agents in one place.
Complete set · 4capabilities
The complete LibreChat capability set.
These are the exact actions your AI can choose when you ask it to work with LibreChat.
01—04
4 capabilities in this set.
Part of 4 available through LibreChat.
- 01 Capability
Login
Login to LibreChat to get access and refresh tokens. This handles authentication so you don't have to manage static keys manually.
- 02 Capability
Chat completions
Create a chat completion using the Agents API by targeting a specific Agent ID. This lets your agent talk directly to your custom setup.
- 03 Capability
List models
List available LibreChat models and agents. Use this to see everything your current instance has to offer.
- 04 Capability
Open responses
Create a response using the Open Responses API to get structured AI outputs. This is useful for getting predictable data formats from your local models.
Set up in minutes
One URL. Then ask LibreChat to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use LibreChat 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_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable LibreChat for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat URL.
- Step 03
Save and start
Save the connection and enable LibreChat in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"librechat": {
"url": "https://edge.vinkius.com/vk_preview_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat
Open Agent mode in chat and ask: "Using LibreChat, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"librechat": {
"url": "https://edge.vinkius.com/vk_preview_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat
Ask Copilot: "Using LibreChat, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"librechat": {
"url": "https://edge.vinkius.com/vk_preview_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat
Open Cascade and ask: "Using LibreChat, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"librechat": {
"url": "https://edge.vinkius.com/vk_preview_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat
Ask Cline: "Using LibreChat, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add librechat --transport http "https://edge.vinkius.com/vk_preview_2Y5OcBZjfHKkJsGbCGI3uDOzGTusTgIZgBtbs3a3/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 LibreChat
Ask Claude: "Using LibreChat, show me...". 4 tools are ready
Where the request belongs
Work LibreChat can move forward.
This is for the privacy-conscious engineer who wants to use self-hosted models without the friction of switching tabs or manually managing API keys.
AI Engineer
Integrates custom-tuned local models into an IDE workflow to test agentic behaviors without using public APIs.
DevOps Engineer
Monitors and queries model configurations across multiple private environments to ensure consistency.
Power User
Centralizes access to various private LLMs into a single chat interface for daily research and drafting.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsCometChat
Enable your AI agent to manage chat users, groups, and messages via the CometChat API.
Rocket.Chat
Connect your AI assistant to Rocket.Chat to seamlessly send messages, explore channels, manage directories, and orchestrate chat operations directly.
SmartChatAI
Manage AI bots, knowledge bases, and messaging on SmartChatAI with AI agents.
Chatsistant
Deploy white-label AI assistants for your clients with custom branding, knowledge bases, and conversation analytics.
Netease Yunxin IM
Equip your AI Agent with Netease Yunxin to massively manage Live Chat Rooms, moderate IM participants, and broadcast messages.
Freshchat
Manage customer conversations, track messages, and oversee agents via AI agents with Freshchat.
Bring your own AI
Change the model, client or framework. Keep LibreChat 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 LibreChat.
The practical details behind the request, access and result.
Does the LibreChat MCP work with my local LLM setup?
Yes, it's specifically designed to bridge your self-hosted LibreChat instance with your AI client. It lets you use your private models directly in your workspace.
Can I use the LibreChat MCP with Cursor or Windsurf?
Absolutely. Since it follows the Connector standard, you can connect it to any compatible client like Cursor, Windsurf, or Claude.
Do I need a static API key to use the LibreChat MCP?
No, you don't have to. While you can use a key, the Connector includes a login capability that allows you to authenticate with your email and password to get session tokens.
How does the LibreChat MCP handle different agents?
It treats your agents as reachable capabilities. You can list them all at once and then tell your AI client which specific agent ID to use for a task.
Is my data private when using the LibreChat MCP?
Yes. Because it connects to your self-hosted instance, your data stays within your infrastructure. The Connector just acts as the bridge between your client and your host.
Can the LibreChat MCP generate structured outputs?
Yes, it supports the Open Responses API, which means you can ask your agent to return specific data formats like JSON instead of just plain text.
How can I see which agents are currently available in my LibreChat instance?
You can use the list_models capability. It will query your configured LibreChat instance and return a list of all accessible agents and models associated with your credentials.
Can I use this server to chat with a specific agent by its ID?
Yes! Use the chat_completions capability. Simply provide the model (which is the Agent ID) and an array of messages to generate a response from that specific agent.
What should I do if I don't have a static API key for my instance?
You can use the login capability. By providing your email and password, the server will authenticate with LibreChat and retrieve the necessary access tokens for subsequent requests.
One connection away
Give your agent a direct line to LibreChat.
Connect LibreChat once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available