How real projects summarise themselves for language models.
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
NYTEMODEONLYllms.txtNYTEMODEONLY/polyterm/llms-full.txt
polyterm agent schemas --format json polyterm agent doctor --skip-network --format json polyterm agent mcp-server polyterm agent jsonl-server ``` All agent-facing tool calls return: ```json { "schema_version
NYTEMODEONLYllms.txtNYTEMODEONLY/polyterm/llms.txt
json` - Doctor: `polyterm agent doctor --skip-network --format json` - FastMCP stdio server: `polyterm agent mcp-server` - Legacy JSON-lines adapter: `polyterm agent jsonl-server` - Static manifest: `docs/tool-manifest.json` - Static schemas: `docs/schemas
Orkas-AIllms.txtOrkas-AI/Orkas-VideoStudio/llms.txt
published. The ovs CLI is the canonical interface, mirrored 1:1 by an MCP server, and can be picked up via native skills, MCP tools, or a self-describing
SirAllapllms.txtSirAllap/agentglass/landing/llms.txt
what the person is signed in to — driven from a CLI and an MCP server. ## Docs - [README](https://raw.githubusercontent.com/SirAllap/agentglass/main/README.md): what it does, screen by screen, platforms, install, FAQ, roadmap
baseReads credentialsllms.txtbase/docs/docs/llms-full.txt
lightweight index of the same pages, use https://docs.base.org/llms.txt. Also available: the [Base MCP server](https://docs.base.org/mcp) for direct AI access to these docs, and [Base skills
basellms.txtbase/docs/docs/llms.txt
resources for AI agents, including docs indexes, MCP access, skills, and recommended starting points - [MCP Server](https://docs.base.org/get-started/docs-mcp): Connect your AI coding assistant to Base documentation using Model Context
raysonmengPipes a download into a shellllms.txtraysonmeng/agent-bridge/site/llms.txt
real time inside one working session. It relays messages between an MCP channel and the Codex app-server protocol so the two agents can cross-review each other's diffs
nirholasllms.txtnirholas/cryptocurrency.cv/llms-full.txt
sources. No API key required. > REST JSON, RSS/Atom, WebSocket, AI analysis, historical archive, MCP server, ChatGPT plugin. > Open source (MIT). https://cryptocurrency.cv This document is the complete inline reference intended
nirholasllms.txtnirholas/cryptocurrency.cv/llms.txt
required. REST JSON, RSS/Atom feeds, WebSocket streaming, AI analysis, historical archive, MCP server, ChatGPT plugin. Source-available (all rights reserved); the hosted API is free to use. Free Crypto News
nirholasllms.txtnirholas/cryptocurrency.cv/public/llms-full.txt
sources. No API key required. > REST JSON, RSS/Atom, WebSocket, AI analysis, historical archive, MCP server, ChatGPT plugin. > Source-available, all rights reserved; the hosted API is free
nirholasllms.txtnirholas/cryptocurrency.cv/public/llms.txt
USDC micropayments via x402. REST JSON, RSS/Atom feeds, WebSocket/SSE streaming, AI analysis, historical archive, MCP server, ChatGPT plugin. > Source-available, all rights reserved; the hosted API is free
rixinhahahallms.txtrixinhahaha/snip/site/llms.txt
return JSON: `{ status, edited, path, text }`. ## Resources - [README](https://github.com/rixinhahaha/snip#readme): Full CLI reference, MCP server setup, install instructions - [GitHub Repository](https://github.com/rixinhahaha/snip): Source code, issues, releases - [Website
claude-did-thisPipes a download into a shellllms.txtclaude-did-this/MCPControl/docs/llms-full.txt
Each client may support different MCP features, allowing for varying levels of integration with MCP servers. ## Feature support matrix | Client | [Resources] | [Prompts] | [Tools] | [Sampling] | Roots | Notes | | ------------------------------------ | ----------- | --------- | ------- | ---------- | ----- | ------------------------------------------------------------------ | | [Claude Desktop App][Claude
danishashkoReads credentialsllms.txtdanishashko/geo-aeo-tracker/cli/llms.txt
retry in a loop. ## Docs - [README](https://github.com/danishashko/geo-aeo-tracker/tree/main/cli#readme) - [Dashboard and MCP server](https://github.com/danishashko/geo-aeo-tracker)
vishalsachdevllms.txtvishalsachdev/canvas-mcp/docs/llms.txt
Canvas MCP > Canvas MCP is an open-source Model Context Protocol (MCP) server that bridges AI assistants with Canvas Learning Management System (LMS). It provides up to 128 tools
bibinprathapllms.txtbibinprathap/VeritasGraph/llms-full.txt
/studio_api/store.py) - Graph engine integration: [studio_api/graphrag_engine.py](./studio_api/graphrag_engine.py) ### Studio Frontend - Single-page UI: [demos/agent-studio/index.html](./demos/agent-studio/index.html) ### MCP Server (Model Context Protocol) - Zero-trust, air-gapped GraphRAG server for local IDE agents (Claude
bibinprathapllms.txtbibinprathap/VeritasGraph/llms.txt
endpoints - GraphRAG pipeline components ## Canonical Paths - Repo root README: [README.md](./README.md) - Cookbook: [cookbook/](./cookbook/) - MCP server (zero-trust, air-gapped GraphRAG over JSON-RPC stdio): [veritasgraph_mcp/](./veritasgraph_mcp/) - Studio backend
allmondayllms.txtallmonday/pydantic-resolve/llms.txt
GraphQL API to AI agents through MCP. ```python from pydantic_resolve import AppConfig, create_mcp_server mcp = create_mcp_server( apps=[ AppConfig( name="blog", er_diagram=diagram, description="Blog
SveltyCMSReads credentialsllms.txtSveltyCMS/SveltyCMS/static/llms.txt
gates. ## Machine-Readable Extras - [OpenAPI Spec](https://demo.sveltycms.com/api/openapi.json): Live generated schema. - [MCP Knowledge Server](https://mcp.sveltycms.com/mcp): Model Context Protocol endpoints for AI agent tool integration. - [GitHub Repository
rife2llms.txtrife2/bld/llms.txt
/rife2/bld/wiki/Custom-Commands): add a project command by writing a method and annotating it with @BuildCommand - [MCP server](https://github.com/rife2/bld/wiki/Standard-Commands#mcp): serve every build command as an MCP tool over stdio, register
A markdown file at a website's root that gives language models a short guide to the site and links to the pages worth reading.
The same idea with the content included, so an agent can read the documentation in one request.
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.
