LangSmith MCP Server ↗

Documentation Index#

Fetch the complete documentation index at: https://docs.langchain.com/llms.txt Use this file to discover all available pages before exploring further.

Use the Model Context Protocol (MCP) server to let language models fetch conversation history, prompts, runs, datasets, experiments, and billing from LangSmith.

The LangSmith MCP Server is a Model Context Protocol (MCP) server that integrates with LangSmith. It lets MCP-compatible clients (for example, AI coding assistants) read conversation history, prompts, runs and traces, datasets, experiments, and billing usage from your LangSmith workspace.

Example use cases#

• Conversation history: “Fetch the history of my conversation from thread ’thread-123’ in project ‘my-chatbot’”
• Prompt management: “Get all public prompts” or “Pull the template for the ’legal-case-summarizer’ prompt”
• Traces and runs: “Fetch the latest 10 root runs from project ‘alpha’” or “Get all runs for a trace by UUID”
• Datasets: “List datasets of type chat” or “Read examples from dataset ‘customer-support-qa’”
• Experiments: “List experiments for dataset ‘my-eval-set’ with latency and cost metrics”
• Billing: “Get billing usage for September 2025”

Use the server in code or Agent Builder

• To connect and use remote MCP servers (including this one) in your Python application, see MCP (Model Context Protocol).
• To connect and use this server in Agent Builder, see Remote MCP servers.

Quickstart (hosted)#

A hosted version of the LangSmith MCP Server is available over HTTP, so you can connect without running the server yourself.

• URL: https://langsmith-mcp-server.onrender.com/mcp
• Authentication: Send your LangSmith API key in the LANGSMITH-API-KEY header.

The hosted instance is for LangSmith Cloud. For a self-hosted LangSmith instance, run the server yourself and point it at your endpoint (see Docker deployment).

Example (Cursor mcp.json):

{
  "mcpServers": {
    "LangSmith MCP (Hosted)": {
      "url": "https://langsmith-mcp-server.onrender.com/mcp",
      "headers": {
        "LANGSMITH-API-KEY": "lsv2_pt_your_api_key_here"
      }
    }
  }
}

Optional headers: LANGSMITH-WORKSPACE-ID, LANGSMITH-ENDPOINT (same as in Environment variables).

Available tools#

The server exposes these tool groups for LangSmith.

Conversation and threads#

Prompt management#

Traces and runs#

Datasets and examples#

Experiments and evaluations#

Billing#

Pagination (character-based)#

Tools that return large payloads use character-budget pagination so responses stay within a size limit:

• Used by: get_thread_history and fetch_runs (when trace_id is set).
• Parameters: Send page_number (1-based) on each request. Optional: max_chars_per_page (default 25000, max 30000), preview_chars (truncate long strings with “… (+N chars)”).
• Response: Includes page_number, total_pages, and the page payload. Request more by calling again with page_number = 2, then 3, up to total_pages.
• Benefits: Pages are built by character count, not item count; no cursor or server-side state—just page numbers.

Installation (run locally)#

If you prefer to run the server locally (or use a self-hosted LangSmith endpoint), install it and configure your MCP client.

Prerequisites#

1. Install uv (Python package installer):

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. Install the package:

   uv run pip install --upgrade langsmith-mcp-server

MCP client configuration#

Add the server to your MCP client config. Use the path from which uvx for the command value.

PyPI / uvx:

{
  "mcpServers": {
    "LangSmith API MCP Server": {
      "command": "/path/to/uvx",
      "args": ["langsmith-mcp-server"],
      "env": {
        "LANGSMITH_API_KEY": "your_langsmith_api_key",
        "LANGSMITH_WORKSPACE_ID": "your_workspace_id",
        "LANGSMITH_ENDPOINT": "https://api.smith.langchain.com"
      }
    }
  }
}

From source (clone langsmith-mcp-server first):

{
  "mcpServers": {
    "LangSmith API MCP Server": {
      "command": "/path/to/uv",
      "args": [
        "--directory",
        "/path/to/langsmith-mcp-server",
        "run",
        "langsmith_mcp_server/server.py"
      ],
      "env": {
        "LANGSMITH_API_KEY": "your_langsmith_api_key",
        "LANGSMITH_WORKSPACE_ID": "your_workspace_id",
        "LANGSMITH_ENDPOINT": "https://api.smith.langchain.com"
      }
    }
  }
}

Replace /path/to/uv, /path/to/uvx, and /path/to/langsmith-mcp-server with your actual paths.

Docker deployment (HTTP-streamable)#

You can run the server as an HTTP service with Docker so clients connect via the HTTP-streamable protocol.

1. Build and run:

   docker build -t langsmith-mcp-server .
   docker run -p 8000:8000 langsmith-mcp-server

   Use the langsmith-mcp-server repository for the Dockerfile and context.

2. Connect your MCP client to http://localhost:8000/mcp with the LANGSMITH-API-KEY header (and optional LANGSMITH-WORKSPACE-ID, LANGSMITH-ENDPOINT).

3. Health check (no auth):

   curl http://localhost:8000/health

For full Docker and HTTP-streamable details, see the LangSmith MCP Server repository.

Deployment overview#

Use the hosted MCP server to connect to LangSmith Cloud (smith.langchain.com or eu.smith.langchain.com). Run the server locally (Installation (run locally)) to connect to Cloud or self-hosted LangSmith (via LANGSMITH_ENDPOINT). If you use self-hosted LangSmith, you can instead run the server via the Docker image in your VPC so it can reach your self-hosted instance.

flowchart LR
  subgraph Client["MCP client"]
    C[Cursor / Claude Code / etc.]
  end

  subgraph CloudPath["Cloud"]
    H[Hosted MCP server]
    LSCloud[LangSmith Cloud]
  end

  subgraph LocalPath["Local"]
    LocalServer[Local MCP server]
  end

  subgraph SelfHostedPath["Self-hosted"]
    D[Docker MCP server]
    LSSelf[Self-hosted LangSmith]
  end

  C --> H
  H --> LSCloud
  C --> LocalServer
  LocalServer --> LSCloud
  LocalServer --> LSSelf
  C --> D
  D --> LSSelf

Environment variables#

For the hosted server, use the same names as headers: LANGSMITH-API-KEY, LANGSMITH-WORKSPACE-ID, LANGSMITH-ENDPOINT.

TypeScript implementation#

A community-maintained TypeScript/Node.js port of the official Python server is available. To run it: LANGSMITH_API_KEY=your-key npx langsmith-mcp-server.

Source and package: GitHub · npm. Maintained by amitrechavia.

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