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The Dash0 MCP Server enables AI assistants to interact with your observability data, allowing them to troubleshoot issues, and interact with metrics, logs, and traces, manage dashboards and alerting rules, and more.
The Dash0 MCP Server is the official Model Context Protocol (MCP) server for Dash0. It enables AI assistants to interact with your observability data, allowing them to troubleshoot issues, and interact with metrics, logs, and traces, manage dashboards and alerting rules, and more.
The MCP server is a "remote" MCP server, cloud-hosted by Dash0. It uses the Streamable HTTP transport, so there is no local process to install or manage. AI assistants connect to it remotely using OAuth 2.0 or a Dash0 auth token.
The Dash0 MCP Server uses the Streamable HTTP transport, running as a cloud-hosted remote service. AI assistants can authenticate using either OAuth 2.0 (recommended for interactive AI tools like Claude Code, Cursor, and Windsurf) or a Dash0 auth token (recommended for CI/CD and automated workflows).
Before configuring the MCP server, ensure:
OAuth 2.0 lets AI assistants authenticate without static API tokens. Dynamic client registration, browser-based consent, and token refresh are handled automatically on first use.
On first use, Claude Code opens a browser window where you log in to Dash0 and grant consent. Access tokens expire after 15 minutes and refresh automatically.
Cursor, Windsurf, and other clients that support remote MCP servers with OAuth can connect using the same MCP endpoint
URL. Add the server through your client's MCP configuration UI or mcp add command, omit the Authorization header,
and the client will walk you through the OAuth consent flow on first connection.
All authorization, token exchange, and revocation events are recorded in your organization's audit logs. You can review and revoke connected applications at any time under User Settings → Applications in Dash0.
For headless environments, scripts, and CI/CD pipelines, configure the server with a static Dash0 auth token.
AI assistants that natively support remote MCP servers can connect directly using the Streamable HTTP transport:
Replace DASH0_MCP_ENDPOINT_URL with your MCP endpoint URL and DASH0_AUTH_TOKEN with your auth token.
For AI assistants that do not yet support remote MCP servers natively, you can use mcp-remote as a bridge: