Chainlit MCP Server for Vercel AI SDK 6 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Chainlit through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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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 Chainlit, 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 Chainlit MCP Server
Connect your Chainlit Cloud projects to any AI agent and embrace a new paradigm of conversational observability. Analyze your AI app traffic directly from your terminal or chat.
The Vercel AI SDK gives every Chainlit tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 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
- Project Analytics — Trigger detailed data fetches mapping global traffic statistics, distinct user adoptions, and absolute utilization figures across your AI portfolio.
- Thread Introspection — Query explicit interaction boundaries isolating full chronological conversations from users securely and swiftly.
- Trace Logic Steps — Extrapolate internal logic jumps identifying explicit prompts, outputs, tool executions, and retrieval boundaries used per interaction.
- Qualitative Feedback — Automatically extract lists capturing precise thumbs up/down, implicit ratings, and explicit textual user reviews targeting your bot responses.
The Chainlit MCP Server exposes 6 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 Chainlit to Vercel AI SDK via MCP
Follow these steps to integrate the Chainlit 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 6 tools from Chainlit and passes them to the LLM
Why Use Vercel AI SDK with the Chainlit MCP Server
Vercel AI SDK provides unique advantages when paired with Chainlit 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 Chainlit integration everywhere
Built-in streaming UI primitives let you display Chainlit 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
Chainlit + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Chainlit MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Chainlit in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Chainlit tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Chainlit capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Chainlit through natural language queries
Chainlit MCP Tools for Vercel AI SDK (6)
These 6 tools become available when you connect Chainlit to Vercel AI SDK via MCP:
get_stats
Retrieve explicit analytics statistics representing traffic boundaries and resource consumptions over native projects
get_thread
Retrieve the exact payload for a specific conversational thread locating exact node topologies
list_feedbacks
List absolute user review feedbacks rating explicitly conversational accuracy and value across deployments
list_projects
List explicit globally configured Chainlit Cloud projects managing independent app tracking spaces
list_steps
List raw programmatic interaction steps explicitly defining prompts and generations inside a single thread
list_threads
List conversational threads identifying user interaction boundaries inside a specific deployed project
Example Prompts for Chainlit in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Chainlit immediately.
"Retrieve the analytics stats of my currently enabled Chainlit cloud project targeting traffic."
"Search my cloud instance for the recent recorded chat interactions (threads) to fetch what clients asked today."
"Gather all negative feedbacks users submitted across this AI project."
Troubleshooting Chainlit MCP Server with Vercel AI SDK
Common issues when connecting Chainlit to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpChainlit + Vercel AI SDK FAQ
Common questions about integrating Chainlit 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 Chainlit 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 Chainlit to Vercel AI SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.