About
The Chronosphere MCP Server provides tools for retrieving logs, metrics, traces, events and configuration entities from a Chronosphere organization, supporting API token or OAuth authentication for integration with MCP clients.
Capabilities
Chronosphere MCP Server
The Chronosphere MCP Server bridges the gap between AI assistants and the rich telemetry ecosystem of Chronosphere. By exposing a set of well‑defined tools for retrieving logs, metrics, traces, and events, the server lets developers query real‑time observability data directly from within an AI workflow. This eliminates the need to manually export or parse logs, enabling instant contextual insights that can be used for debugging, performance tuning, or automated incident response.
At its core, the server implements the Model Context Protocol (MCP) specification, offering a uniform interface for client tools such as Claude Code, VS Code, Cursor, and Codex. Authentication is handled via a Chronosphere API token or OAuth, giving teams the flexibility to use existing security mechanisms. Once authenticated, developers can invoke a curated set of tools—like , , or —to fetch specific resources from their Chronosphere organization. The server also supports configuration queries, allowing assistants to discover available dashboards or mapping rules without hard‑coding any details.
Key capabilities include:
- Unified data access: A single endpoint exposes logs, metrics, traces, and events, simplifying the client‑side logic.
- Secure integration: Token or OAuth authentication keeps data access compliant with enterprise policies.
- Extensibility: New tools can be added via the MCP framework, enabling future expansion to other Chronosphere services.
- Real‑time context: AI assistants can retrieve live telemetry data on demand, providing up‑to‑date information for troubleshooting or monitoring.
Typical use cases involve AI‑powered debugging assistants that can pull the latest log tail or metric trend when a developer asks why a service is underperforming. In incident management, an AI bot can surface relevant traces or alerts from Chronosphere to help root‑cause analysis. Continuous monitoring dashboards can be auto‑generated by an assistant, pulling configuration data from Chronosphere without manual scripting.
By integrating seamlessly into popular IDEs and AI platforms, the Chronosphere MCP Server empowers developers to harness observability data directly within their coding environment. This tight coupling reduces context switching, accelerates problem resolution, and turns raw telemetry into actionable knowledge—all delivered through a standardized MCP interface.
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