> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-consol-1763754753-4714c41.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LangSmith Tool Server

The LangSmith Tool Server is our MCP Framework that powers the tools available in the LangSmith Agent Builder. This framework enables you to build and deploy custom tools that can be integrated with your agents. It provides a standardized way to create, deploy, and manage tools with built-in authentication and authorization.

The PyPi package that defines the framework is available [here](https://pypi.org/project/langsmith-tool-server/).

## Quick start

Install the LangSmith Tool Server and LangChain CLI:

```bash theme={null}
pip install langsmith-tool-server
pip install langchain-cli-v2
```

Create a new toolkit:

```bash theme={null}
langchain tools new my-toolkit
cd my-toolkit
```

This creates a toolkit with the following structure:

```
my-toolkit/
├── pyproject.toml
├── toolkit.toml
└── my_toolkit/
    ├── __init__.py
    ├── auth.py
    └── tools/
        ├── __init__.py
        └── ...
```

Define your tools using the `@tool` decorator:

```python theme={null}
from langsmith_tool_server import tool

@tool
def hello(name: str) -> str:
    """Greet someone by name."""
    return f"Hello, {name}!"

@tool
def add(x: int, y: int) -> int:
    """Add two numbers."""
    return x + y

TOOLS = [hello, add]
```

Run the server:

```bash theme={null}
langchain tools serve
```

Your tool server will start on `http://localhost:8000`.

## Simple client example

Here's a simple example that lists available tools and calls the `add` tool:

```python theme={null}
import asyncio
import aiohttp

async def mcp_request(url: str, method: str, params: dict = None):
    async with aiohttp.ClientSession() as session:
        payload = {"jsonrpc": "2.0", "method": method, "params": params or {}, "id": 1}
        async with session.post(f"{url}/mcp", json=payload) as response:
            return await response.json()

async def main():
    url = "http://localhost:8000"

    tools = await mcp_request(url, "tools/list")
    print(f"Tools: {tools}")

    result = await mcp_request(url, "tools/call", {"name": "add", "arguments": {"a": 5, "b": 3}})
    print(f"Result: {result}")

asyncio.run(main())
```

## Adding OAuth authentication

For tools that need to access third-party APIs (like Google, GitHub, Slack, etc.), you can use OAuth authentication with [Agent Auth](/langsmith/agent-auth).

Before using OAuth in your tools, you'll need to configure an OAuth provider in your LangSmith workspace settings. See the [Agent Auth documentation](/langsmith/agent-auth) for setup instructions.

Once configured, specify the `auth_provider` in your tool decorator:

```python theme={null}
from langsmith_tool_server import tool, Context
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build

@tool(
    auth_provider="google",
    scopes=["https://www.googleapis.com/auth/gmail.readonly"],
    integration="gmail"
)
async def read_emails(context: Context, max_results: int = 10) -> str:
    """Read recent emails from Gmail."""
    credentials = Credentials(token=context.token)
    service = build('gmail', 'v1', credentials=credentials)
    # ... Gmail API calls
    return f"Retrieved {max_results} emails"
```

Tools with `auth_provider` must:

* Have `context: Context` as the first parameter
* Specify at least one scope
* Use `context.token` to make authenticated API calls

***

<Callout icon="pen-to-square" iconType="regular">
  [Edit the source of this page on GitHub.](https://github.com/langchain-ai/docs/edit/main/src/langsmith/agent-builder-mcp-framework.mdx)
</Callout>

<Tip icon="terminal" iconType="regular">
  [Connect these docs programmatically](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
</Tip>