AG-UI is an event-based protocol that lets AI agent backends communicate with user-facing applications. It standardizes agent events and inputs while supporting transports such as server-sent events, WebSockets, and webhooks. The catalogue add-ons help developers build integrations and applications around the protocol.
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.
npx skills add ag-ui-protocol/ag-ui --skill agui-dotnet-multimodalgit clone --depth 1 https://github.com/ag-ui-protocol/ag-uiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ag-ui-protocol/ag-ui/agui-dotnet-multimodal)<a href="https://agentmods.dev/skills/ag-ui-protocol/ag-ui/agui-dotnet-multimodal"><img src="https://agentmods.dev/badge/skills/ag-ui-protocol/ag-ui/agui-dotnet-multimodal/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ag-ui-protocol/ag-ui/agui-dotnet-multimodal"><img src="https://agentmods.dev/badge/skills/ag-ui-protocol/ag-ui/agui-dotnet-multimodal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00186 | $0.00766 |
| Opus 5 | $0.00093 | $0.00383 |
| Sonnet 5 | $0.00037 | $0.00153 |
| Haiku 4.5 | $0.00019 | $0.00077 |
Grade A, and why
agui-dotnet-multimodal 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AG-UI .NET — multimodal messages
Goal: include an image (or other binary content) in a turn so a multimodal model can describe or reason about it.
A multimodal message is an ordinary Microsoft.Extensions.AI ChatMessage whose Contents mixes a TextContent with one or more binary parts. AGUIChatClient carries those parts across the AG-UI wire; the server streams the model's reply as usual.
Install
dotnet add package AGUI.Client
Microsoft.Extensions.AI supplies ChatMessage, TextContent, DataContent, and UriContent.
Attach inline bytes
Use DataContent(bytes, mediaType) to embed the data directly in the message:
using AGUI.Client;
using Microsoft.Extensions.AI;
byte[] imageBytes = await File.ReadAllBytesAsync("photo.png");
var messages = new List<ChatMessage>
{
new(ChatRole.User,
[
new TextContent("Describe this image"),
new DataContent(imageBytes, "image/png"),
]),
};
await foreach (var update in client.GetStreamingResponseAsync(messages))
{
Console.Write(update.Text);
}
The media type must match the bytes (image/png, image/jpeg, audio/wav, application/pdf, …) so the model decodes them correctly.
Reference a hosted URL
When the asset already lives at a URL, use UriContent(uri, mediaType) instead — the bytes never pass through your process:
new ChatMessage(ChatRole.User,
[
new TextContent("What's in this picture?"),
new UriContent("https://example.com/cat.jpg", "image/jpeg"),
]);
Prefer UriContent to reference an asset already hosted at a URL; use DataContent for local bytes the model host can't reach by URL.
Anti-patterns
- Sending a large asset as inline
DataContent. Inline binary is base64-encoded into the request, inflating it ~33% and forcing the whole payload through memory on both ends. For anything sizable that is reachable by URL, sendUriContentand let the model host fetch it. - Targeting a model that isn't multimodal. The content parts cross the wire fine, but a text-only deployment ignores or rejects the image. Point the server's
IChatClientat a vision-capable model/deployment.
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.
- 9d ago First seen · 71 lines · 186 tokens per session scan A 93ce14e44e4e
agui-dotnet-multimodal is a skill published in the GitHub repository ag-ui-protocol/ag-ui (15,782 stars, last pushed yesterday), licensed MIT. It adds 186 tokens to every session and 766 once invoked, about $0.0009 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.
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