activeing123llms.txtmcptoon
activeing123/mcptoon/docs/llms.txt
mcptoon > Zero-dependency Python CLI that finds, unifies and serves MCP servers for every AI client on one machine. > Measured, not advertised: listing 255 tools across 50 servers costs
llms.txt examples
How real projects summarise themselves for language models.
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activeing123llms.txt
xixihhhhllms.txthotclip
xixihhhh/hotclip/docs/llms.txt
click hands-off mode, 24/7 folder watch for stream recordings, headless CLI, local MCP server, Claude Code / Codex agent skill - Publish & survive (v0.14): transform score previewed before export (pixel-level
AmrDabPipes a download into a shellllms.txtclawd-cursor
AmrDab/clawd-cursor/docs/llms.txt
clawdcursor > The local MCP server that gives any tool-calling agent safe control of the real > desktop — clicks, types, reads the screen, opens apps, drives any GUI. Local-only > (binds
neoneyeReads credentialsllms.txtPlanExe
neoneye/PlanExe/public/llms.txt
billing, and API key management. - No public REST API on this host. AI-facing MCP server: - https://mcp.planexe.org/mcp - https://mcp.planexe.org/mcp/ (for clients that require trailing slash) Agent discovery
AceDataCloudllms.txtNexior
AceDataCloud/Nexior/public/llms.txt
Documentation](https://docs.acedata.cloud): Comprehensive guides and API reference - [GitHub](https://github.com/AceDataCloud): Open source MCP servers and clients
Keesan12llms.txtmartin-loop
Keesan12/martin-loop/llms-full.txt
compatible agent hosts use the MartinLoop workflow directly. Install: `npx -y @martinloop/mcp@latest` The MCP server uses local stdio transport for the public package. Through MCP, a host
mcpwarellms.txtcross-code-organizer
mcpware/cross-code-organizer/llms.txt
Cross-Code Organizer (CCO) > Organize Claude Code memories, skills, MCP servers, commands, agents, rules, hooks, plans, sessions, and config across scopes. ## Docs - [AI Index](https://github.com/mcpware/cross-code-organizer/blob/main/AI_INDEX.md): Canonical AI-oriented
gizmodatallms.txtgizmosql
gizmodata/gizmosql/docs/llms.txt
docs.gizmosql.com/opentelemetry.md): traces and metrics export ## Integrations - [Extensions & Tools](https://docs.gizmosql.com/integrations.md): ecosystem integrations - [MCP Server](https://github.com/gizmodata/gizmosql-mcp): Model Context Protocol server and Claude Desktop extension so AI agents
CatCatUnclellms.txtopenworkbuddy
CatCatUncle/openworkbuddy/llms.txt
creation. It supports bring-your-own LLM providers, local Claude Code/Codex engines, Markdown skills, MCP connectors, IM channels, local traces and an executable DAG canvas for short-drama assets. ## Best
openaccountantsllms.txtopenaccountants
openaccountants/openaccountants/llms-full.txt
/api/bundle/CA-ON` **Option 2 — Raw file URL:** Read individual skill files via raw.githubusercontent.com. **Option 3 — MCP server:** `https://www.openaccountants.com/api/mcp` — provides `list_skills`, `get_skill`, `get_skill_sections`, and structured
openaccountantsllms.txtopenaccountants
openaccountants/openaccountants/llms.txt
/api/bundle/CA-ON` **Option 2 — Raw file URL:** Read individual skill files via raw.githubusercontent.com. **Option 3 — MCP server:** `https://www.openaccountants.com/api/mcp` — provides `list_skills`, `get_skill`, `get_skill_sections`, and structured
oxbshwllms.txtwatch-skill
oxbshw/watch-skill/llms.txt
Install the workspace: ```bash npx --yes @deepwatch/cli setup npx --yes @deepwatch/cli web --workspace ./my-project ``` MCP server configuration: ```json { "mcpServers": { "watch-skill": { "command": "uvx", "args": ["--from", "watch-skill[standard]", "watch-skill
griddynamicsPipes a download into a shellllms.txtrosetta
griddynamics/rosetta/llms-full.txt
upgrade = switch to latest. All releases uploaded to RAGFlow as separate datasets; MCP serves latest-stable only. Server-controlled VERSION (clients don't set it) → managed rollouts, no drift
daymoniollms.txtdaymon
daymonio/daymon/docs/llms-full.txt
fails (ideal for monitoring) - **never**: Never nudge How it works: 1. Task completes in MCP server or sidecar 2. Checks task's nudge_mode via `shouldNudgeTask()` 3. Checks quiet hours
daymoniollms.txtdaymon
daymonio/daymon/docs/llms.txt
shell) - **Sidecar** standalone Node.js HTTP server (cron scheduler, file watchers, task execution, embeddings) - **MCP Server** (stdio transport) for Claude Desktop and Claude Code integration - **Shared modules** used by both sidecar
brycewang-stanfordllms.txtStatsPAI
brycewang-stanford/StatsPAI/llms.txt
install statspai` (`pip install "statspai[fixest,plotting]"` for high-dimensional fixed effects and figures). MCP server: `statspai-mcp`. CLI: `statspai`. ## Start here - [AGENTS.md](AGENTS.md): how an agent discovers, calls
mediar-aillms.txtmcp-server-macos-use
mediar-ai/mcp-server-macos-use/llms.txt
mcp-server-macos-use > MCP server for macOS desktop automation using native accessibility APIs ## Overview mcp-server-macos-use is a Model Context Protocol (MCP) server written in Swift that
NYTEMODEONLYllms.txtpolyterm
NYTEMODEONLY/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.txtpolyterm
NYTEMODEONLY/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
mindroom-aiReads credentialsllms.txtmindroom / references
mindroom-ai/mindroom/skills/mindroom-docs/references/llms-full.txt
connect to 100+ tools, including Gmail, Google Drive, Slack, Jira, Confluence, GitHub, and any MCP server ([Tools](https://docs.mindroom.chat/tools/), [MCP Servers](https://docs.mindroom.chat/mcp/)), and search knowledge bases built
About llms.txt
What is llms.txt?
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.
What's llms-full.txt?
The same idea with the content included, so an agent can read the documentation in one request.
Who reads it?
Agents and tools that fetch documentation on someone's behalf. It's a proposal, not a standard, and support varies.
How do I write one?
Start with a one-line summary, then sections of links with a sentence each. The examples here show what real projects do.