实验性本地 stdio 管理服务;需先启动 127.0.0.1:4194 管理端,内容发布仍需人工审批。
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io.github.iannil/ai-slot-management-mcp is an MCP server that 实验性本地 stdio 管理服务;需先启动 127.0.0.1:4194 管理端,内容发布仍需人工审批。. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 87/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"io-github-iannil-ai-slot-management-mcp": {
"args": [
"-y",
"@ai-slot/mcp"
],
"command": "npx"
}
}
}Are you the author?
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实验性本地 stdio 管理服务;需先启动 127.0.0.1:4194 管理端,内容发布仍需人工审批。
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npx -y '@ai-slot/mcp' 2>&1 | head -1 && echo "✓ Server started successfully"
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AI-SLOT adds local AI content and component composition to existing sites, CMSs and site builders. AI produces validated component-tree JSON using developer-registered components. Endpoints can also supply the same protocol without calling AI for every update. After initial integration, supported content updates do not require a host redeploy. A local reference implementation now supports versioned publishing and management MCP; it has protocol tests, while external Agent use and customer deployment remain unverified. The website MCP still reads documentation only. See the delivery status.
Wrap a region of your page and provide the initial HTML as fallback. The runtime keeps a copy for recovery when it replaces the visible content:
<ai-slot name="hero" src="/ai-render/hero">
<section class="hero">
<h1>Our product</h1>
<p>A normal product intro.</p>
</section>
</ai-slot>
Behind that element sits a delivery pipeline: a stateless server proxy turns model output into a validated component tree — never HTML — rendered as your real components, served from a two-tier cache, streamed skeleton-first, and re-pushed when the underlying data changes. If the model times out, invents a component name, or violates a prop schema, the original markup above silently stays. The initial HTML supplies fallback content independently of the model; indexing, accessibility and uptime still depend on the host application.
Content reaches a slot in three ways — visitor personalization is only one of them:
| Delivery mode | Trigger | Path |
|---|---|---|
| Pregenerated | your build (prewarm.mjs) | baked into ai-cache.json, long-TTL cache, no runtime LLM calls on cache hits |
| Live | a data-source change | invalidation push re-renders the slot on every open tab — no redeploy |
| Personalized | a visitor prompt (editable) | sanitized, rate-limited, short TTL — scoped to that one slot |
Prerequisites: Node ≥ 18, pnpm (corepack enable). No API key needed — the demo ships with a deterministic mock LLM.
git clone https://github.com/iannil/ai-slot-component
cd ai-slot-component
pnpm install && pnpm build
node examples/plain-html/server.mjs
# → open http://localhost:4173
The demo app opens with an industry picker — e-commerce, hotel, news and banking pages, each a realistic legacy page. The hero slot carries stream + live, and a recommendation slot whose AI always fails shows the silent fallback. There is no input box on the page — the operator is the one who adjusts: the admin.html ops console (or POST /admin/prompt?slot=<slotId>&prompt=<new prompt>) changes the selling-point angle, POST /admin/publish?slot=<slotId> simulates a data-source change, and both push invalidation so open pages update in place. node examples/plain-html/prewarm.mjs bakes ai-cache.json for the pregenerated path. The project website embeds the same pages as an interactive, step-guided demo running the real runtime in your browser, and the demo app itself is als