plan_my_training — Almost Fire MCP Prompt
plan_my_training
is one of 3 prompts on the
Almost Fire
MCP server. Connect the server and it appears in your client, ready to invoke.
by client
How to invoke plan_my_training from your client
- Claude Code Almost Fire Prompt/plan_my_training run in your project directory
- Claude Desktop Almost Fire Prompt/plan_my_training ~/Library/Application Support/Claude/claude_desktop_config.json
- Cursor Almost Fire Prompt/plan_my_training ~/.cursor/mcp.json
- VS Code Almost Fire Prompt/plan_my_training .vscode/mcp.json
- Zed Almost Fire Prompt/plan_my_training ~/.config/zed/settings.json
- Windsurf Almost Fire Prompt/plan_my_training ~/.codeium/windsurf/mcp_config.json
- Cline Almost Fire Prompt/plan_my_training ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Gemini CLI Almost Fire Prompt/plan_my_training ~/.gemini/settings.json
- Grok Almost Fire Prompt/plan_my_training .mcp.json (in your project root)
- ChatGPT Almost Fire Prompt/plan_my_training Settings → Connectors → Advanced → Developer mode
- Claude.ai Almost Fire Prompt/plan_my_training Settings → Connectors → Add custom connector
- LangChain Almost Fire Prompt/plan_my_training pip install langchain-mcp-adapters
Other prompts on this server
Almost Fire also offers 6 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 8 November 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.