ai-core/ag-ui-protocol

Server-side support for the AG-UI protocol, a standard way for an AI service to stream typed events to a user interface. It covers messages, tool calls, run status, errors, and state updates over web streams.

In plain words
What is it for?
Building server endpoints that stream chat and agent events, receiving agent inputs, handling tool calls, reporting run progress, and sending state changes.
Why use it?
It removes the need to design a separate streaming format for every AI application. The supplied helpers turn agent output into common SSE or NDJSON responses.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/tanstack/ai/ag-ui-protocol
Any agent
npx skills add TanStack/ai --skill ag-ui-protocol
Clone the repo
git clone --depth 1 https://github.com/TanStack/ai

Made for: Claude Code, Codex.

Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,477 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00094 $0.03477
Opus 5 $0.00047 $0.01739
Sonnet 5 $0.00019 $0.00695
Haiku 4.5 $0.00009 $0.00348

Measured 2d ago against content hash 58d774027186, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-core/ag-ui-protocol scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/ai/skills/ai-core/ag-ui-protocol/SKILL.md · 335 lines

How it starts

The opening of the file, as written. The whole thing — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AG-UI Protocol

This skill builds on ai-core. Read it first for critical rules.

Setup — Server Endpoint Producing AG-UI Events via SSE

import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'

export async function POST(request: Request) {
  const { messages } = await request.json()
  const stream = chat({
    adapter: openaiText('gpt-5.2'),
    messages,
  })
  return toServerSentEventsResponse(stream)
}

chat() returns an AsyncIterable<StreamChunk>. Each StreamChunk is a typed AG-UI event (discriminated union on type). The toServerSentEventsResponse() helper encodes that iterable into an SSE-formatted Response with correct headers.

Setup — Receiving AG-UI RunAgentInput on the Server

import {
  chat,
  chatParamsFromRequestBody,
  mergeAgentTools,
  toServerSentEventsResponse,
} from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai/adapters'
import { serverTools } from './tools'

export async function POST(req: Request) {
  let params
  try {
    params = await chatParamsFromRequestBody(await req.json())
  } catch (error) {
    return new Response(
      error instanceof Error ? error.message : 'Bad request',
      { status: 400 },
    )
  }

  const stream = chat({
    adapter: openaiText('gpt-4o'),
    messages: params.messages,
    tools: mergeAgentTools(serverTools, params.tools),
  })

  return toServerSentEventsResponse(stream)
}

chatParamsFromRequestBody validates the body against RunAgentInputSchema from @ag-ui/core. mergeAgentTools merges the server's tool registry with client-declared tools (server wins on collision; client-only tools become no-execute stubs that flow through the runtime's ClientToolRequest path).

params.messages is a mixed array of TanStack UIMessage anchors (with parts) and AG-UI fan-out duplicates ({role:'tool',...}, {role:'reasoning',...}). The existing convertMessagesToModelMessages (called inside chat()) handles dedup automatically.

Read the full file on GitHub · 335 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 335 lines · 94 tokens per session scan A 58d774027186

Subscribe to this mod's changes

ai-core/ag-ui-protocol is a skill published in the GitHub repository TanStack/ai (3,056 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 3,477 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.