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Automated /llms.txt & Agent Documentation Context Compiler
Automated /llms.txt & Agent Documentation Context Compiler is a paid API for AI agents from mcp-compiler.agentdiet.dev, paid per call via MPP, $0.01/call, status unknown (last checked 2026-10-21).
Crawls any documentation or SaaS website and generates a standards-compliant /llms.txt manifest plus JSON-LD schema bundle for AI agent consumption
Price / call$0.01
Success—
StatusUnknown
How this service works
Crawls any documentation or SaaS site and compiles a standards-compliant /llms.txt manifest and JSON-LD schema bundle. (Live x402 v2, IETF MPP & MCP endpoint at https://mcp-compiler.agentdiet.dev/v1/discovery-manifest)
Output
A standards-compliant /llms.txt manifest and accompanying JSON-LD schema bundle derived from the crawled website, structured for direct AI agent and MCP/A2A tool consumption. Includes distilled documentation context ready to be ingested by language model agents.
Example use cases
API docs agent discovery setup
“Crawl the documentation at https://docs.openai.com and generate an llms.txt manifest and JSON-LD schema bundle so my AI agents can automatically discover and reference those docs.”
SaaS onboarding context for agents
“Take the website https://notion.so and compile a standards-compliant /llms.txt manifest from it so I can feed my agent fleet accurate, up-to-date product context without manually summarizing anything.”
Internal tool discoverability packaging
“I have internal documentation at https://docs.mycompany.internal — can you crawl it and produce a ready-to-consume /llms.txt and JSON-LD schema bundle my MCP agents can pull from?”
Technical details
Endpoint
GEThttps://mcp-compiler.agentdiet.dev/v1/discovery-manifest?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to make any existing documentation or SaaS website immediately consumable by AI agents without manually writing an /llms.txt file. Ideal for bootstrapping agent discovery for third-party APIs, onboarding agents to new tools, or packaging documentation context for MCP/A2A pipelines. Prefer this over manual summarization when the site structure is complex or frequently updated.
Side effects
- Invalid or unreachable URL returns an error — site must be publicly accessible
- Private or auth-gated documentation may return incomplete or empty manifests
- Very large sites may produce truncated output or time out
- Dynamically rendered JavaScript-heavy pages may not be fully crawled
- Malformed URL input returns a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| urlrequired | string | Website URL to crawl and generate a ready-to-consume /llms.txt manifest for |
Output
Schema · Response
{
"type": "object"
}Reviews
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