# The Grafana AI SDK for Go: a shared foundation for building AI applications

DevFeed: [The Grafana AI SDK for Go: a shared foundation for building AI applications](<https://devfeed.tech/articles/the-grafana-ai-sdk-for-go-a-shared-foundation-for-building-ai-applications-8593.md>)

Original publisher: [Read original article](<https://grafana.com/blog/the-grafana-ai-sdk-for-go-a-shared-foundation-for-building-ai-applications/>)

Author: Luccas Quadros

Published: 2026-09-12T11:22:06.456390Z

Content type: article

Language: en

Sources: [Grafana Labs blog on Grafana Labs](<https://devfeed.tech/sources/grafana-labs-blog-on-grafana-labs.md>)

Topics: [vercel ai sdk](<https://devfeed.tech/topics/vercel-ai-sdk.md>), [SDKs](<https://devfeed.tech/topics/sdks.md>), [Go Language](<https://devfeed.tech/topics/go-language.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [agent observability](<https://devfeed.tech/topics/agent-observability.md>), [Model Context Protocol](<https://devfeed.tech/topics/model-context-protocol.md>), [React](<https://devfeed.tech/topics/react.md>)

Tags: [agent-observability](<https://devfeed.tech/tags/agent-observability.md>), [ai](<https://devfeed.tech/tags/ai.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [backend](<https://devfeed.tech/tags/backend.md>), [building](<https://devfeed.tech/tags/building.md>), [go](<https://devfeed.tech/tags/go.md>), [grafana](<https://devfeed.tech/tags/grafana.md>), [logs](<https://devfeed.tech/tags/logs.md>), [metrics](<https://devfeed.tech/tags/metrics.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [observability](<https://devfeed.tech/tags/observability.md>), [sdk](<https://devfeed.tech/tags/sdk.md>), [streaming](<https://devfeed.tech/tags/streaming.md>), [tools](<https://devfeed.tech/tags/tools.md>), [traces](<https://devfeed.tech/tags/traces.md>)

## AI overview

Grafana Labs introduces the Grafana AI SDK for Go, an open-source shared foundation for building AI applications. The SDK standardizes model calls, streaming, tool execution, structured output, multi-step agents, workflow controls, and operational features such as retries, logging, metrics, and Agent Observability. It also supports streaming Go backends to Vercel AI SDK frontend hooks.

## Source excerpt

Starting an experiment with an LLM has never been easier. Keeping a growing collection of those experiments consistent is another matter. Earlier this year, as more teams began exploring AI features here at Grafana Labs, we repeatedly encountered the same pattern: a new experiment would start, move quickly, and build its own client for whichever model provider it needed. The next experiment would do the same, with a slightly different abstraction for streaming, tools, errors, or provider configuration. This was understandable, given the circumstances. Model providers were changing quickly, our teams were learning quickly, and coding agents made it possible to turn an idea into a working integration faster than ever. But that speed also made it easier for every integration to develop its own architecture. Eventually, we were maintaining a collection of solutions to what was essentially the same problem. And since most of our backend is written in Go, we built the Grafana AI SDK for Go to give our teams a shared foundation to work from. It provides common interfaces for calling models, streaming responses, executing tools, producing structured output, and running multi-step agents. It also speaks the protocol used by Vercel AI SDK frontend hooks, so a Go backend can stream directly to useChat, useCompletion, and useObject. We built it because we needed it inside Grafana Labs, but we open sourced it last month (alongside a broader collection of tools we released for building, operating, and understanding AI systems during our first Grafana Labs AI Week) because we think other teams building AI applications in Go are likely to encounter many of the same problems. We would like to build the next part together, so in this blog I'll tell you a bit more about the project, including how you can put it to use today, as well as how you can help us improve it. What teams can build with it today The SDK supports both simple model calls and larger application workflows: Generate