X MCP & Agent Tooling

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llms.txt & llms-full.txt Fresh ​

Two machine-readable documentation files give AI tools structured access to the X API docs.

  • llms.txt - a structured index of all documentation pages (titles, URLs, short descriptions). Gives AI tools a map of what is available.
  • llms-full.txt - the complete documentation in a single Markdown file for maximum context.

The llms.txt standard is like a sitemap for AI. It helps LLMs understand documentation structure and find relevant content - similar to how sitemap.xml helps search engines.

The file family ​

FileWhat it containsBest for
llms.txtCurated root index plus links to section indexesQuick overview and agent entry point
x-api/llms.txt370+ X API v2 reference pagesPosts, Users, DMs, Streams, Compliance, etc.
enterprise-api/llms.txtEnterprise, Account Activity, GNIP, WebhooksHistorical and real-time enterprise data
x-ads-api/llms.txtAds API (campaigns, creatives, audiences, analytics)Advertising and measurement
xdks/python/llms.txt + xdks/typescript/llms.txtFull SDK client and model referencesPython and TypeScript/JavaScript developers
llms-full.txtThe entire docs as one Markdown fileMaximum context for deep reasoning

These files (plus the section-specific indexes) are available at the root and under /.well-known/. Every documentation page supports the .md suffix for clean Markdown - for example, a post-lookup reference page is retrievable by appending .md to its URL.

How to use it ​

Start with AGENTS.md

For agents, read AGENTS.md first for explicit usage guidance, then use the files below.

Most AI tools accept URLs directly - provide the URL and the tool fetches and parses the content:

  • Grok: paste https://docs.x.com/llms-full.txt into the chat and ask questions about the X API
  • Cursor / Windsurf: add https://docs.x.com/llms-full.txt as documentation context for your project
  • Custom agents: fetch the file programmatically and include it in your system prompt or context window

Fetch recipes ​

bash
# Fetch the documentation index
curl https://docs.x.com/llms.txt

# Fetch the complete documentation
curl https://docs.x.com/llms-full.txt

# Fetch any individual page as Markdown (append .md)
curl https://docs.x.com/tools/llms-txt.md

Choosing between them ​

flowchart TD
    Q{What does the agent need?} -->|A map of the docs| A[llms.txt]
    Q -->|One specific page| B[Append .md to the page URL]
    Q -->|A whole section| C[Section llms.txt e.g. x-api/llms.txt]
    Q -->|Everything, deep reasoning| D[llms-full.txt]

See also ​