Set Up

Learn how to set up Sentry MCP Monitoring

Sentry MCP Monitoring helps you track and debug Model Context Protocol (MCP) implementations using our supported SDKs and integrations. Monitor your complete MCP workflows from client connections to server responses, including tool executions, resource access, and protocol communications.

To start sending MCP data to Sentry, make sure you've created a Sentry project for your MCP-enabled repository and follow the guide below:

The example below uses @modelcontextprotocol/sdk 1.x. The Sentry wrapper automatically captures spans for MCP server workflows, including tool executions, resource access, and client connections.

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import * as Sentry from "@sentry/node";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";

// Sentry init needs to be above everything else
Sentry.init({
  dsn: "___PUBLIC_DSN___",
  tracesSampleRate: 1.0,
});

// Wrap every MCP server instance
const server = Sentry.wrapMcpServerWithSentry(
  new McpServer({
    name: "my-mcp-server",
    version: "1.0.0",
  }),
);

...

Stable @modelcontextprotocol/server 2.x support requires Sentry JavaScript SDK version 10.70.0 or newer. For framework-specific setup, see MCP Monitoring for Node.js, Hono, or Cloudflare.

The recordInputs and recordOutputs options require Sentry JavaScript SDK version 10.33.0 or newer.

Type: boolean

Records inputs to MCP tool and prompt calls (such as tool arguments and prompt parameters).

Defaults to dataCollection.genAI.inputs. In Sentry JavaScript SDK 10.x, when dataCollection isn't configured, this follows sendDefaultPii.

Type: boolean

Records outputs from MCP tool and prompt calls (such as tool results and prompt messages).

Defaults to dataCollection.genAI.outputs. In Sentry JavaScript SDK 10.x, when dataCollection isn't configured, this follows sendDefaultPii.

MCP work on Cloudflare can finish after the Worker returns an HTTP response. Configure traceLifecycle: "stream" so spans are sent when they finish instead of depending on a static request snapshot. This requires @sentry/cloudflare version 10.49.0 or newer.

See MCP Monitoring on Cloudflare for the configuration and filtering differences in stream mode.

The Sentry Python SDK supports MCP Monitoring for the MCP Python SDK (both low-level and FastMCP APIs) and standalone FastMCP. The integration automatically captures spans for your MCP server workflows, including tool executions, resource access, and prompt handling.

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import sentry_sdk
from sentry_sdk.integrations.mcp import MCPIntegration
from mcp.server.fastmcp import FastMCP

# Sentry init needs to be above everything else
sentry_sdk.init(
    dsn="___PUBLIC_DSN___",
    traces_sample_rate=1.0,
    # Optional: Enable to capture tool call arguments and results in Sentry, which may include PII
    send_default_pii=True,
    integrations=[MCPIntegration()],
)

# Create the MCP server
mcp = FastMCP("Example MCP Server")

# Define a tool
@mcp.tool()
async def calculate_sum(a: int, b: int) -> int:
    """Add two numbers together."""
    return a + b

# Run the server
mcp.run()
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