> For the complete documentation index, see [llms.txt](https://docs.duplocloud.com/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.duplocloud.com/docs/getting-started/integrating-mcp-servers.md). # Integrating MCP Servers DuploCloud's AI platform supports the **Model Context Protocol (MCP)**, an open standard that enables AI agents to connect directly to external tools and services. Through the DuploCloud AI Studio, administrators can register any MCP-compatible server as a provider integration, giving the AI agent live, contextual access to third-party observability, incident management, source control, and other platforms. Once an MCP server is registered, it is attached to a provider scope alongside credentials and resource configuration. At session start, the DuploCloud agent automatically constructs the appropriate MCP configuration and injects it into the agent's environment — no manual setup required for end users. This integration is designed to extend the agent's capabilities beyond infrastructure management. With connected MCP servers, the agent can query error logs, inspect monitors, triage incidents, browse repositories, and take action across platforms — all through natural language, from within a single interface. DuploCloud supports **API key and token-based authentication** for MCP servers via HTTP headers configured in the provider scope's Resource Map. Note that **OAuth-based authentication is not currently supported** — MCP servers requiring an interactive OAuth flow cannot be connected through the DuploCloud platform at this time. Providers already modelled in the platform include observability tools like Datadog, New Relic, and Sentry, incident management platforms like PagerDuty and Incident.io, and source control providers like GitHub and GitLab — making DuploCloud's AI agent a central hub for cross-platform infrastructure intelligence. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.duplocloud.com/docs/getting-started/integrating-mcp-servers.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.