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MCP server for Langsmith SDK integration

Project description

🦜🛠️ LangSmith MCP Server

[!WARNING] LangSmith MCP Server is under active development and many features are not yet implemented.

LangSmith MCP Hero

License: MIT Python 3.10

A production-ready Model Context Protocol (MCP) server that provides seamless integration with the LangSmith observability platform. This server enables language models to fetch conversation history and prompts from LangSmith.

📋 Overview

The LangSmith MCP Server bridges the gap between language models and the LangSmith platform, enabling advanced capabilities for conversation tracking, prompt management, and analytics integration.

🛠️ Installation Options

📝 General Prerequisites

  1. Install uv (a fast Python package installer and resolver):

    curl -LsSf https://astral.sh/uv/install.sh | sh
    
  2. Clone this repository and navigate to the project directory:

    git clone https://github.com/langchain-ai/langsmith-mcp-server.git
    cd langsmith-mcp-server
    

🔌 MCP Client Integration

Once you have the LangSmith MCP Server, you can integrate it with various MCP-compatible clients. You have two installation options:

📦 From PyPI

  1. Install the package:

    uv run pip install --upgrade langsmith-mcp-server
    
  2. Add to your client MCP config:

    {
        "mcpServers": {
            "LangSmith API MCP Server": {
                "command": "/path/to/uvx",
                "args": [
                    "langsmith-mcp-server"
                ],
                "env": {
                    "LANGSMITH_API_KEY": "your_langsmith_api_key"
                }
            }
        }
    }
    

⚙️ From Source

Add the following configuration to your MCP client settings:

{
    "mcpServers": {
        "LangSmith API MCP Server": {
            "command": "/path/to/uvx",
            "args": [
                "--directory",
                "/path/to/langsmith-mcp-server/langsmith_mcp_server",
                "run",
                "server.py"
            ],
            "env": {
                "LANGSMITH_API_KEY": "your_langsmith_api_key"
            }
        }
    }
}

Replace the following placeholders:

  • /path/to/uv: The absolute path to your uv installation (e.g., /Users/username/.local/bin/uv). You can find it running which uv.
  • /path/to/langsmith-mcp-server: The absolute path to your langsmith-mcp project directory
  • your_langsmith_api_key: Your LangSmith API key

Example configuration:

{
    "mcpServers": {
        "LangSmith API MCP Server": {
            "command": "/Users/mperini/.local/bin/uvx",
            "args": [
                "langsmith-mcp-server"
            ],
            "env": {
                "LANGSMITH_API_KEY": "lsv2_pt_1234"
            }
        }
    }
}

Copy this configuration in Cursor > MCP Settings.

LangSmith Cursor Integration

🧪 Development and Contributing 🤝

If you want to develop or contribute to the LangSmith MCP Server, follow these steps:

  1. Create a virtual environment and install dependencies:

    uv sync
    
  2. To include test dependencies:

    uv sync --group test
    
  3. View available MCP commands:

    uvx langsmith-mcp-server
    
  4. For development, run the MCP inspector:

    uv run mcp dev langsmith_mcp_server/server.py
    
    • This will start the MCP inspector on a network port
    • Install any required libraries when prompted
    • The MCP inspector will be available in your browser
    • Set the LANGSMITH_API_KEY environment variable in the inspector
    • Connect to the server
    • Navigate to the "Tools" tab to see all available tools
  5. Before submitting your changes, run the linting and formatting checks:

    make lint
    make format
    

🚀 Example Use Cases

The server enables powerful capabilities including:

  • 💬 Conversation History: "Fetch the history of my conversation with the AI assistant from thread 'thread-123' in project 'my-chatbot'"
  • 📚 Prompt Management: "Get all public prompts in my workspace"
  • 🔍 Smart Search: "Find private prompts containing the word 'joke'"
  • 📝 Template Access: "Pull the template for the 'legal-case-summarizer' prompt"
  • 🔧 Configuration: "Get the system message from a specific prompt template"

🛠️ Available Tools

The LangSmith MCP Server provides the following tools for integration with LangSmith:

Tool Name Description
list_prompts Fetch prompts from LangSmith with optional filtering. Filter by visibility (public/private) and limit results.
get_prompt_by_name Get a specific prompt by its exact name, returning the prompt details and template.
get_thread_history Retrieve the message history for a specific conversation thread, returning messages in chronological order.
get_project_runs_stats Get statistics about runs in a LangSmith project, either for the last run or overall project stats.
fetch_trace Fetch trace content for debugging and analyzing LangSmith runs using project name or trace ID.
list_datasets Fetch LangSmith datasets with filtering options by ID, type, name, or metadata.
list_examples Fetch examples from a LangSmith dataset with advanced filtering options.
read_dataset Read a specific dataset from LangSmith using dataset ID or name.
read_example Read a specific example from LangSmith using the example ID and optional version information.

📄 License

This project is distributed under the MIT License. For detailed terms and conditions, please refer to the LICENSE file.

Made with ❤️ by the LangChain Team

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