LangSmith (LLM Observability & Hub) MCP Server for Mastra AI 6 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect LangSmith (LLM Observability & Hub) through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
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Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"langsmith-llm-observability-hub": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "LangSmith (LLM Observability & Hub) Agent",
instructions:
"You help users interact with LangSmith (LLM Observability & Hub) " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with LangSmith (LLM Observability & Hub)?"
);
console.log(result.text);
}
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.
Mastra's agent abstraction provides a clean separation between LLM logic and LangSmith (LLM Observability & Hub) tool infrastructure. Connect 6 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
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 Mastra AI 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 Mastra AI via MCP
Follow these steps to integrate the LangSmith (LLM Observability & Hub) MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 6 tools from LangSmith (LLM Observability & Hub) via MCP
Why Use Mastra AI with the LangSmith (LLM Observability & Hub) MCP Server
Mastra AI provides unique advantages when paired with LangSmith (LLM Observability & Hub) through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add LangSmith (LLM Observability & Hub) without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every LangSmith (LLM Observability & Hub) tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
LangSmith (LLM Observability & Hub) + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the LangSmith (LLM Observability & Hub) MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query LangSmith (LLM Observability & Hub), process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed LangSmith (LLM Observability & Hub) as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query LangSmith (LLM Observability & Hub) on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using LangSmith (LLM Observability & Hub) tools alongside other MCP servers
LangSmith (LLM Observability & Hub) MCP Tools for Mastra AI (6)
These 6 tools become available when you connect LangSmith (LLM Observability & Hub) to Mastra AI 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 Mastra AI
Ready-to-use prompts you can give your Mastra AI 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 Mastra AI
Common issues when connecting LangSmith (LLM Observability & Hub) to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpLangSmith (LLM Observability & Hub) + Mastra AI FAQ
Common questions about integrating LangSmith (LLM Observability & Hub) MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
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 Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.