what_should_i_train_today — anatome MCP Prompt

what_should_i_train_today is one of 8 prompts on the anatome MCP server. Connect the server and it appears in your client, ready to invoke.

by client

How to invoke what_should_i_train_today from your client

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

Other prompts on this server

• log_my_day
• review_my_week
• plan_my_week
• import_my_history
• check_my_progress
• am_i_eating_enough_protein
• export_my_data

anatome also offers 8 resources — data you attach as context, where a prompt is something you run.

Read from the server itself, by connecting to it and calling prompts/list on 24 September 2026. A listing does not declare its prompts, 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 prompt's arguments.