llms.txt — how agents use AgentReady — audit MCP Resource

llms.txt — how agents use AgentReady is one of 4 resources on the audit MCP server. Connect the server and your client can attach it as context.

by client

How to attach llms.txt — how agents use AgentReady from your client

• Claude Code audit Resource/llms.txt — how agents use AgentReady run in your project directory
• Claude Desktop audit Resource/llms.txt — how agents use AgentReady ~/Library/Application Support/Claude/claude_desktop_config.json
• Cursor audit Resource/llms.txt — how agents use AgentReady ~/.cursor/mcp.json
• VS Code audit Resource/llms.txt — how agents use AgentReady .vscode/mcp.json
• Zed audit Resource/llms.txt — how agents use AgentReady ~/.config/zed/settings.json
• Windsurf audit Resource/llms.txt — how agents use AgentReady ~/.codeium/windsurf/mcp_config.json
• Cline audit Resource/llms.txt — how agents use AgentReady ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
• Gemini CLI audit Resource/llms.txt — how agents use AgentReady ~/.gemini/settings.json
• Grok audit Resource/llms.txt — how agents use AgentReady .mcp.json (in your project root)
• ChatGPT audit Resource/llms.txt — how agents use AgentReady Settings → Connectors → Advanced → Developer mode
• Claude.ai audit Resource/llms.txt — how agents use AgentReady Settings → Connectors → Add custom connector
• LangChain audit Resource/llms.txt — how agents use AgentReady pip install langchain-mcp-adapters

Other resources on this server

• Pricing
• AgentReady-spec conformance
• Agent-Ready Index

Read from the server itself, by connecting to it and calling resources/list on 24 September 2026. A listing does not declare its resources, so asking is the only way to know them, and this is what the server actually offers rather than what its listing claims. Names only are stored; connect the server for each resource's type and contents.