Integrate LangSmith (LLM Observability & Hub) with Claude, Cursor, Chatbots & AI Agents MCP Server

Q: 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.

Monitor LLM apps via LangSmith — track traces, audit prompt templates, and manage evaluation datasets.

GDPR Free for Subscribers

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

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Get run on LangSmith (LLM Observability & Hub)

Get precise telemetry for a single LLM invocation run

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List annotation queues on LangSmith (LLM Observability & Hub)

List active human-in-the-loop annotation queues

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List datasets on LangSmith (LLM Observability & Hub)

List all evaluation and fine-tuning datasets mapped in LangSmith

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List projects on LangSmith (LLM Observability & Hub)

Maps out the boundaries of distinct AI pipelines currently monitored by LangSmith. List all active LangSmith tracing projects/sessions

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List prompts on LangSmith (LLM Observability & Hub)

Extract prompt templates hosted in the LangChain Hub

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List runs on LangSmith (LLM Observability & 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

Security & Code Integrity Audit

Every tool in the LangSmith (LLM Observability & Hub) MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.

A+Score: 100

How Vinkius protects your data

Is there a risk of the AI "going crazy" and deleting important company data?

No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.

Can I set different limits for each virtual assistant on my team?

Absolutely. You have full control in our command center. You can create an AI agent that only "reads" data so the support team can answer questions, and another superpowered agent that can "edit" and "create" information exclusively for your operations team. Each AI gets exactly the level of access you allow.

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.

What happens if the underlying API rate limits my agent?

Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.

Automated Workflows using LangSmith (LLM Observability & Hub)

Use LangSmith (LLM Observability & Hub) with any AI agent framework to process, analyze, and mutate data securely via the Model Context Protocol.

Next-Gen llm observability Automation

The LangSmith (LLM Observability & Hub) MCP integration translates natural language prompts into structured llm observability queries. This allows agents to fetch and update superpower records securely.

Cursor Copilot for tracing

Deploy the LangSmith (LLM Observability & Hub) toolkit to manage tracing. The integration offers robust endpoints for ChatGPT to control superpower settings.