LiteLLM (LLM Proxy & Spend Tracking) MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect LiteLLM (LLM Proxy & Spend Tracking) through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using LiteLLM (LLM Proxy & Spend Tracking), list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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
About LiteLLM (LLM Proxy & Spend Tracking) MCP Server
Connect your LiteLLM Proxy instance to any AI agent and take full control of your LLM infrastructure, load balancing, and spend management through natural conversation.
The Vercel AI SDK gives every LiteLLM (LLM Proxy & Spend Tracking) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Key Orchestration — Generate and manage proxy API keys to isolate distinct microservices or teams, including precise budget and rate limit constraints directly from your agent
- Model Routing Intelligence — Get detailed info on fallback paths (e.g., OpenAI -> Anthropic -> Groq) and verify exact routing endpoints assigned to your models
- Real-time Spend Audit — Track total USD consumed by specific end-users or teams and monitor budget ceilings to ensure cost-effective AI deployments
- Dynamic Model Control — Inject fresh routing endpoints (e.g., new AWS Bedrock or Azure OpenAI deployments) into your proxy runtime with zero downtime
- Team & Organizational Isolation — Create and manage team profiles to track exact cost limits and operational boundaries per organizational division
- Infrastructure Security — Instantly vaporize malicious or leaked keys and remove broken LLM deployments to prevent downstream 500 errors dynamically
The LiteLLM (LLM Proxy & Spend Tracking) MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect LiteLLM (LLM Proxy & Spend Tracking) to Vercel AI SDK via MCP
Follow these steps to integrate the LiteLLM (LLM Proxy & Spend Tracking) MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from LiteLLM (LLM Proxy & Spend Tracking) and passes them to the LLM
Why Use Vercel AI SDK with the LiteLLM (LLM Proxy & Spend Tracking) MCP Server
Vercel AI SDK provides unique advantages when paired with LiteLLM (LLM Proxy & Spend Tracking) through the Model Context Protocol.
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 LiteLLM (LLM Proxy & Spend Tracking) integration everywhere
Built-in streaming UI primitives let you display LiteLLM (LLM Proxy & Spend Tracking) tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
LiteLLM (LLM Proxy & Spend Tracking) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the LiteLLM (LLM Proxy & Spend Tracking) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query LiteLLM (LLM Proxy & Spend Tracking) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate LiteLLM (LLM Proxy & Spend Tracking) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed LiteLLM (LLM Proxy & Spend Tracking) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with LiteLLM (LLM Proxy & Spend Tracking) through natural language queries
LiteLLM (LLM Proxy & Spend Tracking) MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect LiteLLM (LLM Proxy & Spend Tracking) to Vercel AI SDK via MCP:
create_model
Inject completely fresh routing endpoints (ex: new Bedrock Llama 4 endpoints)
create_team
Generate pristine organizational isolation tracking exact cost limits per division
create_user
Insert specific End-User identities bridging Vinkius with Proxy logs
delete_key
Delete an existing LLM proxy key entirely
delete_model
Delete explicitly routed LLM deployments preventing 500s dynamically
generate_key
Generate a new proxy API key isolating distinct microservices or teams
get_key_info
Get configuration and budget bounds for a specific LiteLLM API Key
get_model_info
Get array endpoints tracing exact Fallback paths like OpenAI -> Anthropic
get_team_info
Get internal logic bounds matching multiple routing users via Team UUID
get_user_info
Return precise End-User abstractions tracking total USD consumed natively
Example Prompts for LiteLLM (LLM Proxy & Spend Tracking) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with LiteLLM (LLM Proxy & Spend Tracking) immediately.
"List all active model fallback paths in LiteLLM"
"Generate a new API key for the 'Customer-Service' team with a $50 monthly budget"
"How much has user 'alex_dev' spent on LLM tokens today?"
Troubleshooting LiteLLM (LLM Proxy & Spend Tracking) MCP Server with Vercel AI SDK
Common issues when connecting LiteLLM (LLM Proxy & Spend Tracking) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpLiteLLM (LLM Proxy & Spend Tracking) + Vercel AI SDK FAQ
Common questions about integrating LiteLLM (LLM Proxy & Spend Tracking) MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
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?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect LiteLLM (LLM Proxy & Spend Tracking) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect LiteLLM (LLM Proxy & Spend Tracking) to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.