Client tools never execute against spec-compliant AG-UI servers (plain success RUN_FINISHED) #1464

TanStack AI version

0.54

Framework/Library version

React 19

Describe the bug and the steps to reproduce it

What happens

When useChat is connected to a third-party AG-UI server (Pydantic AI's AGUIAdapter in my case), the model calls a registered .client() tool, the tool call is rendered, and then the run just ends. The .client() handler is never invoked and no continuation run is started.

The server emits the canonical AG-UI sequence for a frontend tool:

TOOL_CALL_START  { toolCallId: "tooluse_…", toolCallName: "ping" }
TOOL_CALL_ARGS   { delta: "" }
TOOL_CALL_END
RUN_FINISHED     { outcome: { type: "success" } }

Why

Client-tool execution is only triggered from StreamProcessor.handleInterrupts (activities/chat/stream/processor.ts), i.e. when RUN_FINISHED carries outcome.type: "interrupt" with a metadata.kind: "client_tool" interrupt. That's the shape TanStack's own chat() emits, but it isn't what AG-UI specifies.

Per ag-ui-protocol/ag-ui#2731, a frontend tool call ends the run with a plain success outcome. It may include pendingToolCallIds; otherwise the client derives the unanswered calls from the stream. The client then executes the tools and continues with role: "tool" messages in the next run's history. There is no success-outcome path that calls onToolCall, so nothing fires.

Expected

On a success RUN_FINISHED, the client should dispatch onToolCall for tool calls that were started but not answered by TOOL_CALL_RESULT, using outcome.pendingToolCallIds when present. The rest of the pipeline already exists (pendingToolExecutions, addToolResultForClientTool, continuation). The interrupt path would stay unchanged.

Repro

1. Pydantic AI agent exposed via AGUIAdapter, no server-side ping tool.
2. useChat({ connection: fetchServerSentEvents(url), tools: [pingDef.client(() => 'pong')] })
3. Ask the agent to call ping and report the result → handler never runs, conversation stops.

Your Minimal, Reproducible Example - (Sandbox Highly Recommended)

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