Coralogix unveiled the official Coralogix MCP (Model Context Protocol) Server, which enables third-party AI agents to connect directly to Coralogix’s observability data, including logs, metrics, traces, SIEM, and real user monitoring (RUM), across production, staging, and other environments.
The MCP Server is available to Coralogix’s 4000+ customers, allowing them to enhance their AI agents with access to detailed observability data, dramatically reducing mean time to resolution (MTTR), streamlining agent workflows, and minimizing engineering overhead.
MCP is an open standard developed by Anthropic, the company behind Claude, that provides a simple way to connect tools, data, and services to AI models and systems. By utilizing Coralogix’s MCP Server, AI agents can directly access detailed information about a customer’s applications and infrastructure. This interaction trains the AI agent, enhancing its capabilities and effectiveness.
Last quarter, Coralogix introduced Olly, the advanced AI observability assistant. Olly is an SRE agent that can fully analyze production systems, understands the full context of logs, metrics, and traces, and surfaces RCA and business impact. Today’s MCP Server announcement brings that same deep Coralogix context to builders: it exposes a secure MCP endpoint so developers can stream live telemetry into their own AI agents, IDEs, or chat-ops workflows; and shape the experience to suit their needs.
Agents generally lack direct access to specific observability data, which limits the AI’s utility for this purpose. What makes Coralogix’s MCP Server unique is its ability to surface observability data that is highly specific to each customer. It can search through data to find custom attributes and entities that reflect the customer's unique setup, leading to more accurate results when AI agents access logs, metrics, and traces. Customers can also use natural language prompts to locate key metrics or events.
By integrating with tools developers already use, such as the widely used AI code editor Cursor or IDEs, the MCP Server enables AI agents to not only detect issues in real time but also assist in diagnosing and resolving them all within the same workflow. This “closing the loop” capability streamlines operations and reduces the need to switch between multiple tools.
“Adding the MCP server to our current AI capabilities will enable teams to create custom AI-driven observability experiences,” said Liran Hason, VP of AI at Coralogix. “Now, our customers can easily equip their AI agents with direct access to production observability data. Publishing an official MCP Server also allows our customers to rely on a trusted MCP source and ensure they get the best and most reliable observability capabilities for their agents.”
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