mcp-collection
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A Python-based tool to interact with Datadog API and fetch monitoring data from your infrastructure.
The Datadog Model Context Protocol (MCP) is a Python-based tool designed to facilitate interaction with the Datadog API, enabling users to efficiently fetch and analyze monitoring data from their infrastructure. This tool provides a streamlined interface for accessing monitor states and Kubernetes logs, making it easier to manage and troubleshoot infrastructure issues. With its modular design and type safety features, the Datadog MCP ensures robust and error-free operations. It leverages the FastMCP framework for tool management, offering a standardized way for AI models to interact with external tools and APIs. The tool is particularly useful for users who need to maintain context across conversations and execute commands in a consistent manner.
Features
- Monitor State Tracking: Fetch and analyze specific monitor states.
- Kubernetes Log Analysis: Extract and format error logs from Kubernetes clusters.
- FastMCP Base: Utilizes FastMCP framework for tool management.
- Modular Design: Separate functions for monitors and logs.
- Type Safety: Full typing support with Python type hints.
Tools
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