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.
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
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
dengyierllms.txtdengyier/OpenWorkProof/llms.txt
immutable audit record for denied requests - CLI (`owp status / run-tests / repo-read`), MCP stdio transport server, AgentTeams TCP network client - Docker production executor with STARTED_UNCONFIRMED crash recovery - Supply
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
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
GabrieleLozuponellms.txtGabrieleLozupone/kokon/site/llms.txt
before/after compare, private mode, works offline after setup. - For AI agents: built-in MCP server (generate_image, edit_image, inpaint_image, outpaint_image, upscale_image, ...) and a local HTTP
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 2.11.6, 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 16 analytical skills that load on demand. MIT, local stdio, v2.11.6. Docs: https://ga4mcp.com
surendranbPipes a download into a shellllms.txtsurendranb/google-analytics-mcp/llms.txt
Google Analytics 4 (GA4) MCP Server > Model Context Protocol (MCP) server for Google Analytics 4 data exploration, schema discovery, and real-time metrics. ## Installation - UVX: `uvx google-analytics-mcp
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
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
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 library, and CLI for AI agents. > Local-first. Apache-2.0. Formerly mcp-video. ## One-line definition Kinocut is an Apache-2.0 open-source
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
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
joshuaswarrenReads credentialsllms.txtjoshuaswarren/openclaw-engram/llms.txt
level commands). Ships `remnic` and legacy `engram` bins. @remnic/server Standalone HTTP + MCP server. Multi-token auth, daemon mode, OAuth facade. Ships `remnic-server` and legacy `engram-server` bins. @remnic/coding-graph
FLOX-Foundationllms.txtFLOX-Foundation/flox/docs/llms-full.txt
language bindings | Python, Node.js, Codon, JavaScript, C API | | AI companion | [`lrvx-mcp`](https://github.com/lrvx/lrvx/tree/main/mcp) — Model Context Protocol server for Cursor / Claude Code / Cline | | Type-safe primitives | Strong types
FLOX-Foundationllms.txtFLOX-Foundation/flox/docs/llms.txt
symbol ## AI tooling (MCP) - [lrvx-mcp — Model Context Protocol server](https://docs.lrvx.dev/mcp/): Local MCP server that gives AI agents grounded access to indicators, error codes
Bitget-AIllms.txtBitget-AI/agent_hub/llms.txt
foundation TypeScript SDK), `bitget-agent-cli` (terminal `bgc` CLI), `bitget-agent-mcp` (desktop MCP server), `bitget-agent-skill` (terminal AI reasoning guide), `bitget-signal` (5 market-analysis skills
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.
