AI Agent for Tempo MCP
Integrate Grafana Tempo distributed tracing with AI assistants using the Tempo MCP Server. Enable powerful trace querying, real-time event streaming, and seamless integration with tools like Claude Desktop, Cursor, and n8n. Get enhanced visibility into distributed systems and streamline trace analysis for faster troubleshooting and insights.
Seamless Grafana Tempo Integration
The Tempo MCP Server allows AI agents to directly query and analyze distributed tracing data from Grafana Tempo. Use model context protocol for secure, efficient trace data access, and integrate with popular AI clients to boost your observability workflow.
- Direct Trace Querying.
- Query Grafana Tempo traces with flexible filtering by service, duration, status, and more through the tempo_query tool.
- MCP Protocol Support.
- Supports Model Context Protocol for secure, extensible integration with leading AI clients like Claude Desktop and Cursor.
- Multi-Mode Communication.
- Operates via stdin/stdout or as an HTTP server with Server-Sent Events (SSE) for real-time integrations.
- Easy Deployment.
- Run locally, with Docker, or Docker Compose for fast setup and scalable deployments.
Real-Time Streaming & Extensible Endpoints
Enable real-time event streaming with the SSE endpoint and speed up trace analysis with dedicated MCP endpoints. Integrate seamlessly with n8n workflows, AI agents, and CI/CD tools for a connected observability stack.
- Server-Sent Events (SSE).
- Get real-time trace data updates with a dedicated SSE endpoint, perfect for n8n and custom workflow automation.
- HTTP & MCP Endpoints.
- Access trace data via HTTP or MCP messaging, supporting flexible integration into modern DevOps pipelines.
- Configurable Authentication.
- Supports basic auth, bearer tokens, and custom URLs for secure, adaptable deployments.
Advanced Trace Analysis for AI Agents
Empower your AI assistants with advanced distributed trace analysis. Use environment variables for configuration, leverage Docker for portability, and integrate with tools like Claude Desktop and Cursor for AI-driven observability.
- Flexible Query Parameters.
- Set custom time ranges, trace limits, and filters for granular trace exploration.
- Environment Variable Support.
- Configure server URLs and ports via environment variables for seamless deployment in any environment.
- AI Assistant Compatibility.
- Works with Claude Desktop, Cursor, and other MCP-compatible AI agents for automated trace-driven insights.
MCP INTEGRATION
Available Tempo MCP Integration Tools
The following tools are available as part of the Tempo MCP integration:
- tempo_query
Query Grafana Tempo trace data using flexible query parameters to find distributed tracing information.
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What is Tempo MCP Server
Tempo MCP Server is a Go-based server implementation for the Model Context Protocol (MCP) that integrates with Grafana Tempo. It enables AI assistants and applications to query, analyze, and interact with distributed tracing data using MCP. This server is designed for developers and organizations seeking to automate and optimize the analysis of distributed systems’ performance. Tempo MCP Server supports easy deployment via Docker and is highly suitable for use cases involving automated data retrieval, AI-driven trace analysis, and integration with advanced developer tools. By providing a standardized protocol interface, it allows seamless communication between AI agents and the powerful tracing capabilities of Grafana Tempo.
Capabilities
What we can do with Tempo MCP Server
Tempo MCP Server enables powerful integrations and automation by allowing AI assistants and applications to interact directly with Grafana Tempo tracing data. It supports querying, analyzing, and retrieving distributed trace data, and can be easily deployed with Docker or Go for fast integration into development and operational workflows.
- Query distributed tracing data
- Retrieve and analyze trace information from Grafana Tempo for in-depth performance diagnostics.
- Integrate with AI assistants
- Enable AI agents to automate and streamline access to tracing data for faster troubleshooting.
- Easy deployment
- Deploy the server using Docker or Go for rapid setup and minimal configuration.
- MCP protocol support
- Standardized interface ensures compatibility with various AI agents and tools.
- Developer-centric workflows
- Enhance productivity by automating repetitive tracing-related tasks through AI integration.
What is Tempo MCP Server
AI agents can benefit from Tempo MCP Server by leveraging its standardized MCP interface to seamlessly interact with distributed tracing data in Grafana Tempo. This enables AI-powered automation, advanced analysis, and rapid diagnostics, enhancing observability workflows and reducing the time to identify and resolve issues in distributed systems.