LangSmith (LLM Observability & Hub) MCP Server
Monitor LLM apps via LangSmith — track traces, audit prompt templates, and manage evaluation datasets.
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What is the LangSmith MCP Server?
The LangSmith MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to LangSmith via 6 tools. Monitor LLM apps via LangSmith — track traces, audit prompt templates, and manage evaluation datasets. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (6)
Tools for your AI Agents to operate LangSmith
Ask your AI agent "List all active tracing projects in LangSmith" and get the answer without opening a single dashboard. With 6 tools connected to real LangSmith data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents 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 and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
LangSmith (LLM Observability & Hub) MCP Server capabilities
6 toolsGet precise telemetry for a single LLM invocation run
List active human-in-the-loop annotation queues
List all evaluation and fine-tuning datasets mapped in LangSmith
Maps out the boundaries of distinct AI pipelines currently monitored by LangSmith. List all active LangSmith tracing projects/sessions
Extract prompt templates hosted in the LangChain Hub
Isolates the raw interactions containing prompts sent to and responses received from the AI models. List explicit LLM invocation runs within a specific project
What the LangSmith (LLM Observability & Hub) MCP Server unlocks
Connect your LangSmith account to any AI agent and take full control of your LLM observability, tracing, and prompt management through natural conversation.
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
How it works
1. Subscribe to this server
2. Enter your LangSmith API Key and Endpoint
3. Start monitoring your LLM infrastructure from Claude, Cursor, or any MCP-compatible client
Who is this for?
- LLM Engineers — debug complex agentic traces and measure prompt performance through natural conversation without manual UI filtering
- AI Developers — retrieve the latest prompt templates from the Hub and verify evaluation dataset structures directly from your workspace
- AI Analysts — audit human feedback queues and report on overall model grounding and accuracy across multiple tracing projects
Frequently asked questions about the LangSmith (LLM Observability & Hub) MCP Server
Can I see the token usage for a specific LLM run through my agent?
Yes. Use the get_run_telemetry tool with a specific Run ID. Your agent will retrieve the exact token count (prompt + completion) and latency metrics calculated by LangSmith for that interaction.
How do I fetch a prompt template from the LangChain Hub using natural language?
The list_prompts tool allows your agent to navigate your hosted Hub repository. You can ask your agent to find a specific prompt by name to inspect its instruction text, variables, and version history.
Can my agent check the status of human annotation queues?
Absolutely. Use the list_annotation_queues tool to retrieve all active queues where human feedback is being collected. Your agent can report on the number of pending traces and general alignment scores established by your reviewers.
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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.
Give your AI agents the power of LangSmith MCP Server
Production-grade LangSmith (LLM Observability & Hub) MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.