diff --git a/docs/ai/monitoring/agents/naming.mdx b/docs/ai/monitoring/agents/naming.mdx
index 0aebb89eca905..bb3efd9aee968 100644
--- a/docs/ai/monitoring/agents/naming.mdx
+++ b/docs/ai/monitoring/agents/naming.mdx
@@ -14,18 +14,18 @@ Sentry uses the `gen_ai.agent.name` span attribute to identify agents in the [AI
 
 ## Quick Reference
 
-| Framework               | Platform | How to Name                                                        |
-| ----------------------- | -------- | ------------------------------------------------------------------ |
-| OpenAI Agents SDK       | Python   | `Agent(name="...")`                                                |
-| Pydantic AI             | Python   | `Agent(..., name="...")`                                           |
-| LangChain               | Python   | `create_agent(model, tools, name="...")`                           |
-| LangGraph               | Python   | `.compile(name="...")` or `create_react_agent(..., name="...")`    |
-| Vercel AI SDK           | JS       | `experimental_telemetry: { functionId: "..." }`                    |
-| LangGraph               | JS       | `.compile({ name: "..." })` or `createReactAgent({ name: "..." })` |
-| LangChain               | JS       | `createAgent({ name: "..." })`                                     |
-| Mastra                  | JS       | `Agent({ id: "...", name: "..." })`                                |
-| .NET (M.E.AI)           | .NET     | `options.Experimental.AgentName = "..."`                           |
-| Other / raw LLM clients | Any      | [Manual instrumentation](#manual-instrumentation)                  |
+| Framework               | Platform | How to Name                                                                          |
+| ----------------------- | -------- | ------------------------------------------------------------------------------------ |
+| OpenAI Agents SDK       | Python   | `Agent(name="...")`                                                                  |
+| Pydantic AI             | Python   | `Agent(..., name="...")`                                                             |
+| LangChain               | Python   | `create_agent(model, tools, name="...")`                                             |
+| LangGraph               | Python   | `.compile(name="...")` or `create_react_agent(..., name="...")`                      |
+| Vercel AI SDK           | JS       | `experimental_telemetry: { functionId: "..." }` on `generateText` or `ToolLoopAgent` |
+| LangGraph               | JS       | `.compile({ name: "..." })` or `createReactAgent({ name: "..." })`                   |
+| LangChain               | JS       | `createAgent({ name: "..." })`                                                       |
+| Mastra                  | JS       | `Agent({ id: "...", name: "..." })`                                                  |
+| .NET (M.E.AI)           | .NET     | `options.Experimental.AgentName = "..."`                                             |
+| Other / raw LLM clients | Any      | [Manual instrumentation](#manual-instrumentation)                                    |
 
 ## Framework Integrations
 
@@ -113,7 +113,7 @@ agent = create_react_agent(model, tools, name="dice_agent")
 
 #### Vercel AI SDK
 
-Vercel AI SDK doesn't have a dedicated agent name field. Instead, set `functionId` in `experimental_telemetry` — Sentry uses this as the agent identifier.
+Set `functionId` in `experimental_telemetry` — Sentry uses this as the agent identifier. This works for both `generateText` and `ToolLoopAgent`:
 
 ```javascript
 import { generateText } from "ai";
@@ -129,6 +129,24 @@ const result = await generateText({
 });
 ```
 
+For the `ToolLoopAgent` class, set `functionId` in the constructor:
+
+```javascript
+import { ToolLoopAgent } from "ai";
+import { openai } from "@ai-sdk/openai";
+
+const agent = new ToolLoopAgent({
+  model: openai("gpt-4o"),
+  tools: {
+    /* ... */
+  },
+  experimental_telemetry: {
+    isEnabled: true,
+    functionId: "weather_agent",
+  },
+});
+```
+
 <PlatformLink
   platform="javascript.node"
   to="/configuration/integrations/vercelai/"
diff --git a/docs/platforms/javascript/common/configuration/integrations/vercelai.mdx b/docs/platforms/javascript/common/configuration/integrations/vercelai.mdx
index 1c6506bfa1546..737c79ba043ef 100644
--- a/docs/platforms/javascript/common/configuration/integrations/vercelai.mdx
+++ b/docs/platforms/javascript/common/configuration/integrations/vercelai.mdx
@@ -84,7 +84,7 @@ Sentry.init({
 </PlatformSection>
 
 <PlatformSection supported={['javascript.cloudflare', 'javascript.nextjs']}>
-To correctly capture spans, pass the `experimental_telemetry` object with `isEnabled: true` to every `generateText`, `generateObject`, and `streamText` function call. For more details, see the [AI SDK Telemetry Metadata docs](https://sdk.vercel.ai/docs/ai-sdk-core/telemetry#telemetry-metadata).
+To correctly capture spans, pass the `experimental_telemetry` object with `isEnabled: true` to every `generateText`, `generateObject`, `streamText`, and `ToolLoopAgent` call. For more details, see the [AI SDK Telemetry Metadata docs](https://sdk.vercel.ai/docs/ai-sdk-core/telemetry#telemetry-metadata).
 
 ```javascript
 const result = await generateText({
@@ -160,6 +160,34 @@ Sentry.init({
 
 </PlatformSection>
 
+## ToolLoopAgent
+
+The integration also captures spans for the [`ToolLoopAgent`](https://ai-sdk.dev/docs/agents/overview#toolloopagent-class) class. Each call to `generate()` or `stream()` creates an agent span with individual LLM requests and tool executions as child spans.
+
+<PlatformSection notSupported={["javascript.cloudflare", "javascript.nextjs"]}>
+
+No additional configuration is needed — `ToolLoopAgent` spans are captured automatically.
+
+</PlatformSection>
+
+<PlatformSection supported={['javascript.cloudflare', 'javascript.nextjs']}>
+
+Pass `experimental_telemetry` with `isEnabled: true` to the `ToolLoopAgent` constructor to correctly capture spans:
+
+</PlatformSection>
+
+```javascript
+const agent = new ToolLoopAgent({
+  model: openai("gpt-4o"),
+  tools: { /* ... */ },
+  experimental_telemetry: { isEnabled: true },
+});
+
+const result = await agent.generate({
+  prompt: "What is the weather in San Francisco?",
+});
+```
+
 ## Identifying functions
 
 In order to make it easier to correlate captured spans with the function calls we recommend setting `functionId` in `experimental_telemetry` in all generation function calls:
@@ -174,6 +202,19 @@ const result = await generateText({
 });
 ```
 
+For `ToolLoopAgent`, set `functionId` in the constructor:
+
+```javascript
+const agent = new ToolLoopAgent({
+  model: openai("gpt-4o"),
+  tools: { /* ... */ },
+  experimental_telemetry: {
+    isEnabled: true,
+    functionId: "weather-agent",
+  },
+});
+```
+
 ## Configuration
 
 By default this integration adds tracing support to all `ai` function callsites. If you need to disable span collection for a specific call, you can do so by setting `experimental_telemetry.isEnabled` to `false` in the first argument of the function call.