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.
KyaniteLabsllms.txtKyaniteLabs/kinocut/docs/llms-full.txt
separate website publication check. ## Identity and release truth Kinocut is an Apache-2.0 MCP server, Python client and CLI for guarded media workflows. KyaniteLabs publishes it. The CLI is kino
KyaniteLabsllms.txtKyaniteLabs/kinocut/llms.txt
Kinocut > Guardrailed video editing MCP server, Python client and CLI for AI agents. > Local-first. Apache-2.0. Formerly mcp-video. Kinocut is an open-source Model Context Protocol (MCP) server
mattrobinsonsrePipes a download into a shellllms.txtmattrobinsonsre/terrapod/llms.txt
Baked into the api + runner images and published standalone. | Go | | `mcp/` | `terrapod-mcp` — official **MCP server**: a local stdio adapter letting an AI agent (Claude, Cursor, …) drive one Terrapod instance
saelounllms.txtsaeloun/miru-web/public/llms-full.txt
OpenAPI: https://app.miru.so/openapi.json - API catalog: https://app.miru.so/.well-known/api-catalog - MCP endpoint: https://app.miru.so/mcp - MCP Server Card: https://app.miru.so/.well-known/mcp/server-card.json - Agent skills: https://app.miru.so/.well-known/agent-skills/index.json - Public product docs: https://miru.so
saelounllms.txtsaeloun/miru-web/public/llms.txt
OpenAPI: https://app.miru.so/openapi.json - API catalog: https://app.miru.so/.well-known/api-catalog - MCP endpoint: https://app.miru.so/mcp - MCP Server Card: https://app.miru.so/.well-known/mcp/server-card.json - Agent skills: https://app.miru.so/.well-known/agent-skills/index.json - Marketing/docs: https://miru.so/docs
clearcotelabsllms.txtclearcotelabs/clearcote-browser/llms.txt
with `--shm-size=1g -p 127.0.0.1:9222:9222 --security-opt seccomp= `; see /docker/README.md. - MCP server: `clearcote-mcp` (PyPI / npm). Profile Manager desktop app 0.12.2 (Windows + Linux): https://github.com/clearcotelabs/clearcote-profile-manager ## Quick
sachitrafallms.txtsachitrafa/YourMemory/llms.txt
entity extraction) - **Protocol:** MCP (Model Context Protocol) stdio server - **API:** FastAPI HTTP server on port 3033 ## MCP Tools - `recall_memory(query, user_id, current_path?)` — hybrid retrieval with graph expansion
kreuzberg-devReads credentialsllms.txtkreuzberg-dev/liter-llm/llms.txt
openai/*", "anthropic/*"] rpm = 60 budget = 50.0 [[providers]] name = "openai" api_key = "${OPENAI_API_KEY}" ## MCP Server Model Context Protocol server with 22 tools matching the REST API. Supports stdio
QVerisAIPipes a download into a shellllms.txtQVerisAI/QVerisAI/agent/llms-full.txt
only the latest Discover ID, endpoint, query, and result summaries for 30 minutes. The MCP server preserves process/session correlation but does not provide semantic route memory. JavaScript and Python
QVerisAIPipes a download into a shellllms.txtQVerisAI/QVerisAI/agent/llms.txt
qverisai/cli — no upfront catalog schemas, deterministic output, API discovery without preloading the catalog - MCP Server v0.15.0 (local stdio fallback): npx @qverisai/mcp — for stdio-only IDE integrations - JavaScript SDK v0.10.0
dengyierllms.txtdengyier/OpenWorkProof/llms.txt
mcp`. The MCP client manages this process. There is no hosted remote endpoint or API key in this setup. `owp` is the separate CLI, not the stdio server. The optional
SentryReads credentialsllms.txtgetsentry/dotagents/docs/public/llms.txt
dotagents > Shared tooling for coding agents dotagents manages agent skills, MCP servers, hooks, subagents, and plugins declared in `agents.toml`, and handles symlinks and config generation so tools like Claude Code
sepehr071llms.txtsepehr071/awesome-iran-mcp/llms.txt
iran-mcp > 77 MCP servers (994 tools) that let AI agents search and compare Iranian websites: Digikala, Torob, Basalam, Technolife, MasterKala, Baneh, Shopino, Banimode, Divar, Khanoumi, Asal Banoo, Snappfood, Okala
vinkius-labsReads credentialsllms.txtvinkius-labs/mcp-fusion/docs/llms.txt
MCP Fusion > fusion is the TypeScript framework for production MCP servers. MVA architecture, structured perception for AI agents — zero hallucination, zero data leaks. ## What is MCP Fusion? MCP Fusion
erikdarlingdatallms.txterikdarlingdata/PerformanceStudio/llms.txt
mismatches, missing indexes, spills, parallel skew, parameter sniffing, implicit conversions, and more. Built-in MCP server for AI-assisted plan analysis. SSMS extension for one-click plan transfer. Runs
surendranbPipes a download into a shellllms.txtsurendranb/google-analytics-mcp/docs/llms-full.txt
MCP Server — full text Version 2.11.7, updated 2026-10-25. https://ga4mcp.com # GA4 MCP client setup — the config each one expects URL: https://ga4mcp.com/ga4-mcp-for-every-harness/ # Every client, and the config
surendranbPipes a download into a shellllms.txtsurendranb/google-analytics-mcp/docs/llms.txt
MCP Server > Model Context Protocol server for Google Analytics 4. Read-only reporting, schema discovery, and 17 analytical skills that load on demand. MIT, local stdio, v2.11.7. Docs: https://ga4mcp.com
oliver-zehentleitnerDeletes or force-pushesllms.txtoliver-zehentleitner/keep-the-why/llms.txt
tree or one-file-per-decision, with no required external service (no database, no MCP server). ## Questions this answers - "My coding agent keeps suggesting something we already tried and rejected
Scottcjnllms.txtScottcjn/beacon-skill/llms.txt
prefixed agent IDs) - **RTC Payments**: Native micropayments attached to beacon envelopes via RustChain integration - **MCP Server**: Beacon's MCP-compatible tool server for Claude Code integration - **beacon-skill**: The Python
AgusMayolllms.txtAgusMayol/optics/public/llms.txt
Cursor Rules & MCPs](https://optics.agusmayol.com.ar/collections/cursor-rules): Guidelines for cursor behavior, multi-cursor patterns, and MCP server integration. ### Next.js Configuration [Next.js ConfigurationSoon](https://optics.agusmayol.com.ar/collections/nextjs-configuration): Future documentation on configuring Next.js with
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.
