MCP
A vendor-neutral OpenTelemetry specification that sets standard span names, attributes, metrics, and events for generative AI work.
A vendor-neutral OpenTelemetry specification that sets standard span names, attributes, metrics, and events for generative AI work. It covers model inference, agent runs, tool execution, and Model Context Protocol calls. Shared attributes like gen_ai.operation.name, gen_ai.request.model, and gen_ai.usage.input_tokens let any compliant tracing backend read telemetry from any instrumented framework. The conventions are still in Development status and now live in their own repository, open-telemetry/semantic-conventions-genai.
Primary source: github.com
Example
Shared attributes like gen_ai.operation.name, gen_ai.request.model, and gen_ai.usage.input_tokens let any compliant tracing backend read telemetry from any instrumented framework.
Hands-on guides, comparisons, and tutorials that cover MCP.
FAQ
A vendor-neutral OpenTelemetry specification that sets standard span names, attributes, metrics, and events for generative AI work.
OpenTelemetry GenAI Semantic Conventions sits in the MCP part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover MCP topics including OpenTelemetry GenAI Semantic Conventions. Check the blog and YouTube channel for hands-on walkthroughs.
Related
A Model Context Protocol extension, made first-class in the 2026-07-28 spec, that gives long-running work a proper home - builds, deployments, long agent runs, and batch jobs that do not finish inside a single request.
Agent identity means giving an AI agent its own verifiable identity, so other systems can authenticate it, limit what it is allowed to do, and log its actions separately from the person it acts for.
A function exposed by an MCP server that an AI agent can call to perform an action.

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