🦜🛠️ LangSmith MCP Server

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

LangSmith MCP Hero

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

Install uv (a fast Python package installer and resolver):
```
curl -LsSf https://astral.sh/uv/install.sh | sh
```

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

Install the package:

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

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:

Create a virtual environment and install dependencies:
```
uv sync
```
To include test dependencies:
```
uv sync --group test
```
View available MCP commands:
```
uvx langsmith-mcp-server
```
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
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