Bring Llm Orchestration
to Vercel AI SDK
Learn how to connect LibreChat to Vercel AI SDK and start using 4 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the LibreChat MCP Server?
Connect your LibreChat instance to any AI agent and gain programmatic control over your self-hosted AI ecosystem. This server allows you to bridge your custom agents and models with any MCP-compatible client.
What you can do
- Agent Orchestration — List all available agents and models configured in your LibreChat environment.
- Unified Completions — Create chat completions using the Agents API, providing an OpenAI-compatible interface for your custom setups.
- Open Responses — Utilize the Open Responses API specification to generate structured AI outputs.
- Session Management — Authenticate directly via email and password to retrieve access tokens when a static API key is not preferred.
How it works
- Subscribe to this server
- Provide your LibreChat Base URL and API Key (or use the login tool)
- Start interacting with your private LLM agents through Claude, Cursor, or other MCP tools.
Who is this for?
- AI Engineers — integrate self-hosted LibreChat agents into automated workflows and IDEs.
- DevOps Teams — monitor and query available model configurations across different environments.
- Power Users — centralize access to multiple private LLMs through a single, secure interface.
Built-in capabilities (4)
Model corresponds to an Agent ID. Create a chat completion using the Agents API
List available LibreChat models/agents
Login to LibreChat to get access and refresh tokens
Create a response using the Open Responses API
Why Vercel AI SDK?
The Vercel AI SDK gives every LibreChat tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 4 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
- —
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
- —
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same LibreChat integration everywhere
- —
Built-in streaming UI primitives let you display LibreChat tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
LibreChat in Vercel AI SDK
LibreChat and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect LibreChat to Vercel AI SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for LibreChat in Vercel AI SDK
The LibreChat MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 4 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Vercel AI SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
LibreChat for Vercel AI SDK
Every tool call from Vercel AI SDK to the LibreChat MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I see which agents are currently available in my LibreChat instance?
You can use the list_models tool. 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 tool. 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 tool. By providing your email and password, the server will authenticate with LibreChat and retrieve the necessary access tokens for subsequent requests.
How does the Vercel AI SDK connect to MCP servers?
Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
Can I use MCP tools in Edge Functions?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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