Coralogix AI Model Context Protocol Server
The Model Context Protocol (MCP) server enables external AI agents to access and analyze Coralogix observability data—logs, metrics, and traces—via a remote streamable HTTP transport-powered interface. Built using an express-based architecture, the server bridges your AI tooling and Coralogix telemetry to support AI-native troubleshooting and root cause analysis.
Use it to:
- Query logs, metrics, and traces from your Coralogix account.
- Execute DataPrime queries with optimized formatting for Cursor and similar tools.
- Investigate issues directly from your IDE and perform root cause analysis.
- Receive AI-generated fix suggestions based on your code and observability data.
- Create, update, and delete alerts and parsing rules from your AI agent.
- Generate Terraform HCL, Kubernetes Operator YAML, and OpenAPI definitions from any alert or parsing rule—existing or newly described.
How it works
The MCP server is based on the Model Context Protocol, an open protocol designed to connect AI assistants with structured data sources and tools. The server functions as a plugin, enabling AI agents to interact with external systems using standardized interfaces.
Supporting data queries, the server provides a seamless way to integrate tools like Cursor with your infrastructure without requiring additional configuration about your project’s structure. Alert, parsing rule, and IaC generation tools are accessible through the same MCP server connection.
Security
The MCP server supports secure access to logs, metrics, and traces through an API key that is unique for each user. Each key is scoped per user, enforcing least-privilege access, and all interactions are designed to be safe, auditable, and compliant.