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LangSmith (LLM Observability & Hub) MCP Server for Cursor 6 tools — connect in under 2 minutes

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Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

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Classic Setup·json
{
  "mcpServers": {
    "langsmith-llm-observability-hub": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}
LangSmith (LLM Observability & Hub)
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

Cursor's Agent mode turns LangSmith (LLM Observability & Hub) into an in-editor superpower. Ask Cursor to generate code using live data from LangSmith (LLM Observability & Hub) and it fetches, processes, and writes — all in a single agentic loop. 6 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

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 Cursor 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 Cursor via MCP

Follow these steps to integrate the LangSmith (LLM Observability & Hub) MCP Server with Cursor.

01

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

02

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

03

Save the file

Cursor will automatically detect the new MCP server

04

Start using LangSmith (LLM Observability & Hub)

Open Agent mode in chat and ask: "Using LangSmith (LLM Observability & Hub), help me..."6 tools available

Why Use Cursor with the LangSmith (LLM Observability & Hub) MCP Server

Cursor AI Code Editor provides unique advantages when paired with LangSmith (LLM Observability & Hub) through the Model Context Protocol.

01

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

02

Cursor's Composer feature can generate entire files using real-time data fetched through MCP — no copy-pasting from external dashboards

03

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

04

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

LangSmith (LLM Observability & Hub) + Cursor Use Cases

Practical scenarios where Cursor combined with the LangSmith (LLM Observability & Hub) MCP Server delivers measurable value.

01

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

02

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

03

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

04

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

LangSmith (LLM Observability & Hub) MCP Tools for Cursor (6)

These 6 tools become available when you connect LangSmith (LLM Observability & Hub) to Cursor via MCP:

01

get_run

Get precise telemetry for a single LLM invocation run

02

list_annotation_queues

List active human-in-the-loop annotation queues

03

list_datasets

List all evaluation and fine-tuning datasets mapped in LangSmith

04

list_projects

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

05

list_prompts

Extract prompt templates hosted in the LangChain Hub

06

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 Cursor

Ready-to-use prompts you can give your Cursor agent to start working with LangSmith (LLM Observability & Hub) immediately.

01

"List all active tracing projects in LangSmith"

02

"Show me the telemetry for the last run in the 'Production-Bot-V2' project"

03

"List all prompts hosted in our Hub repository"

Troubleshooting LangSmith (LLM Observability & Hub) MCP Server with Cursor

Common issues when connecting LangSmith (LLM Observability & Hub) to Cursor through the Vinkius, and how to resolve them.

01

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.
02

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

LangSmith (LLM Observability & Hub) + Cursor FAQ

Common questions about integrating LangSmith (LLM Observability & Hub) MCP Server with Cursor.

01

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.
02

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.
03

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design — tool calls require user visibility and approval.
04

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.

Connect LangSmith (LLM Observability & Hub) to Cursor

Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.