plan_field_task — Agent Groundcrew MCP Prompt
plan_field_task
is one of 1 prompt on the
Agent Groundcrew
MCP server. Connect the server and it appears in your client, ready to invoke.
by client
How to invoke plan_field_task from your client
- Claude Code Agent Groundcrew Prompt/plan_field_task run in your project directory
- Claude Desktop Agent Groundcrew Prompt/plan_field_task ~/Library/Application Support/Claude/claude_desktop_config.json
- Cursor Agent Groundcrew Prompt/plan_field_task ~/.cursor/mcp.json
- VS Code Agent Groundcrew Prompt/plan_field_task .vscode/mcp.json
- Zed Agent Groundcrew Prompt/plan_field_task ~/.config/zed/settings.json
- Windsurf Agent Groundcrew Prompt/plan_field_task ~/.codeium/windsurf/mcp_config.json
- Cline Agent Groundcrew Prompt/plan_field_task ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Gemini CLI Agent Groundcrew Prompt/plan_field_task ~/.gemini/settings.json
- Grok Agent Groundcrew Prompt/plan_field_task .mcp.json (in your project root)
- ChatGPT Agent Groundcrew Prompt/plan_field_task Settings → Connectors → Advanced → Developer mode
- Claude.ai Agent Groundcrew Prompt/plan_field_task Settings → Connectors → Add custom connector
- LangChain Agent Groundcrew Prompt/plan_field_task pip install langchain-mcp-adapters
Agent Groundcrew also offers 4 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 14 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.