Datadog Intros MCP Server for Secure AI Observability

Datadog, Inc., a provider of observability and security services for cloud applications, has announced that its MCP Server is now generally available. 

The Datadog MCP Server provides access to live observability data, enabling teams to debug using their preferred AI coding agents or an Integrated Development Environment, with real-time telemetry, and take action within established security and governance controls.

Enabling the next stage of AI-native development

According to Datadog, the new program was created specifically for developers embedding AI agents into development and operational workflows, particularly as AI agent integration becomes more common across industries.

The Datadog MCP Server is designed to provide secure, governed access to production data, enabling engineering teams to operationalize AI agents and navigate the process with reduced integration overhead while maintaining compatibility with compliance standards.

“Datadog delivers AI solutions that transform complexity into clarity and blind spots into security, helping protect global businesses and make operations seamless. We are always listening to our customers and the biggest problems they are facing in their day-to-day work, which is why we are excited to launch our MCP Server as the latest way to help teams become more efficient in using Datadog to build and scale AI systems across their organizations,” said Yanbing Li, chief product officer at Datadog. 

“By combining telemetry from Datadog’s unified observability platform into teams’ AI workflows, we are enabling the next stage of AI-native development—moving from simply AI copilots to AI operating on live production systems,” Li continued.

MCP server extends observability into agentic workflows

Datadog says its new MCP Server provides a purpose-built interface designed for agentic systems. 

It extends Datadog’s unified observability platform directly into AI workflows, allowing engineering teams to:

• Debug and act quickly without context switching: Feeds live logs, metrics, and traces directly into AI coding agents like Codex, Claude Code, and Cursor when investigating production issues.
• Give custom AI agents direct access to real-time observability and intelligence: Empowers agents to leverage Datadog’s proactive detection and remediation signals to investigate and respond to issues automatically.
• Simplify data access for AI workflows: Reduces the risk of breaking changes by providing a dynamic, purpose-built protocol for agent communication.

Addressing AI complexity in the dev lifecycle 

According to Li, the Datadog MCP Server release aims to reduce the complexity of AI-enabled development and unlock greater innovation.

“AI compounds complexity, especially with its pace of innovation,” Li said.

“Datadog is helping to solve that complexity for customers with launches like MCP Server by enabling autonomy across Dev, Ops and Security teams so that they can not only detect, decide and act on issues within Datadog, but also build, deliver and evaluate software throughout the development process,” Li added.

The Datadog MCP Server is now available and can be accessed here.

Last year, Datadog acquired autonomous QA testing platform Propolis, enabling agents to infer user intent from how applications are used. Learn more about the move and other industry shakeups in our January 2026 M&A Recap.