LangSmith (LLM Observability & Hub) 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 LangSmith (LLM Observability & Hub) through the 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 LangSmith (LLM Observability & Hub), 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 LangSmith (LLM Observability & Hub) MCP Server
Connect your LangSmith account to any AI agent and take full control of your LLM observability, tracing, and prompt management through natural conversation.
The Vercel AI SDK gives every LangSmith (LLM Observability & Hub) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 6 tools through the 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
- Trace Orchestration — List active tracing projects and retrieve detailed execution logs for specific LLM invocation runs directly from your agent
- Performance Telemetry — Extract precise metrics including token consumption, prompt latency, and exact error strings from your AI pipelines
- Prompt Hub Access — Navigate and retrieve managed prompt templates, variable definitions, and version histories hosted in the LangChain Hub
- Evaluation Datasets — Enumerate curated 'golden' datasets used for automated evaluation of prompt logic or few-shot injection models
- Human-in-the-Loop Audit — Monitor active annotation queues where human reviewers assess the alignment, accuracy, and safety of generated LLM traces
- Agentic Step Analysis — Deep-dive into multi-turn agentic workflows to understand nested tool calls and internal reasoning paths securely
The LangSmith (LLM Observability & Hub) 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 LangSmith (LLM Observability & Hub) to Vercel AI SDK via MCP
Follow these steps to integrate the LangSmith (LLM Observability & Hub) 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 LangSmith (LLM Observability & Hub) and passes them to the LLM
Why Use Vercel AI SDK with the LangSmith (LLM Observability & Hub) MCP Server
Vercel AI SDK provides unique advantages when paired with LangSmith (LLM Observability & Hub) 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 LangSmith (LLM Observability & Hub) integration everywhere
Built-in streaming UI primitives let you display LangSmith (LLM Observability & Hub) 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
LangSmith (LLM Observability & Hub) + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the LangSmith (LLM Observability & Hub) MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query LangSmith (LLM Observability & Hub) in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate LangSmith (LLM Observability & Hub) tools and return structured JSON responses to any frontend
Chatbots with tool use: embed LangSmith (LLM Observability & Hub) capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with LangSmith (LLM Observability & Hub) through natural language queries
LangSmith (LLM Observability & Hub) MCP Tools for Vercel AI SDK (6)
These 6 tools become available when you connect LangSmith (LLM Observability & Hub) to Vercel AI SDK via MCP:
get_run
Get precise telemetry for a single LLM invocation run
list_annotation_queues
List active human-in-the-loop annotation queues
list_datasets
List all evaluation and fine-tuning datasets mapped in LangSmith
list_projects
Maps out the boundaries of distinct AI pipelines currently monitored by LangSmith. List all active LangSmith tracing projects/sessions
list_prompts
Extract prompt templates hosted in the LangChain Hub
list_runs
Isolates the raw interactions containing prompts sent to and responses received from the AI models. List explicit LLM invocation runs within a specific project
Example Prompts for LangSmith (LLM Observability & Hub) in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with LangSmith (LLM Observability & Hub) immediately.
"List all active tracing projects in LangSmith"
"Show me the telemetry for the last run in the 'Production-Bot-V2' project"
"List all prompts hosted in our Hub repository"
Troubleshooting LangSmith (LLM Observability & Hub) MCP Server with Vercel AI SDK
Common issues when connecting LangSmith (LLM Observability & Hub) to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpLangSmith (LLM Observability & Hub) + Vercel AI SDK FAQ
Common questions about integrating LangSmith (LLM Observability & Hub) 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 LangSmith (LLM Observability & Hub) 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 LangSmith (LLM Observability & Hub) to Vercel AI SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.