by traceloop · MCP Server · ★ 192
OpenTelemetry MCP Server Query and analyze LLM traces with AI assistance. Ask Claude to find expensive API calls, debug errors, compare model performance, or track token usage—all from your IDE. An MCP (Model Context Protocol) server that connects AI assistants to OpenTelemetry trace backends (Jaeger, Tempo, Traceloop), with specialized support for LLM observability through OpenLLMetry semantic conventions.
| Stars | 192 |
| Forks | 22 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 74.7362628346684/100 |
| Open Issues | 18 |
| Last Updated | 2026-06-21 |
| Created | 2025-11-02 |
| Platforms | mcp, python |
| Est. Tokens | ~19k |
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opentelemetry-mcp-server is Unified MCP server for querying OpenTelemetry traces across multiple backends (Jaeger, Tempo, Traceloop, etc.), enabling AI agents to analyze distributed traces for automated debugging and observabili. It is categorized as a MCP Server with 192 GitHub stars.
opentelemetry-mcp-server is primarily written in Python.
You can find installation instructions and usage details in the opentelemetry-mcp-server GitHub repository at github.com/traceloop/opentelemetry-mcp-server. The project has 192 stars and 22 forks, indicating an active community.
opentelemetry-mcp-server is released under the Apache-2.0 license, making it free to use and modify according to the license terms.