Grok Bot MCP
Related Servers
Alternatives to Grok Bot MCP
No user-submitted related servers found.
Related Servers
- AlicenseCqualityCmaintenanceEnables IDEs and MCP hosts to drive a user's Grok Bot cloud agents, including sending messages, waiting for replies, reading history, and managing agents, secrets, widgets, handoffs, and desktop access. It acts as an outbound bridge from Cursor, Claude, and VS Code to those cloud agents.21MIT
- FlicenseNot gradedqualityDmaintenanceAutomates Grok web interface to provide chat, web search, and conversation management via MCP, supporting multiple accounts and local/remote deployment.-
- AlicenseNot gradedqualityBmaintenanceAn MCP server that lets agents delegate work to Grok Bot desktop app bots by sending messages, waiting for and reading replies, checking weekly usage, and creating, renaming, or deleting Bots. It drives the locally running app over its debug port, so any MCP client can hand tasks to an always-on bot.2MIT
- AlicenseNot gradedqualityCmaintenanceEnables MCP clients such as Claude Code to message configured Grok Bot agents and receive their replies through a local, token-authenticated HTTP MCP endpoint backed by Cursor's BDK. It runs on macOS and Windows and supports asking, checking, listing, and interrupting bot tasks.113 npmMIT
- AlicenseAqualityBmaintenanceEnables any MCP client such as Cursor, Claude Code, or Codex to dispatch tasks to a Cursor Grok Bot running on its cloud computer, poll for its replies, and interrupt an in-progress run. It also lists the bots available for contact, without routing replies through an extra model.41MIT
- AlicenseAqualityBmaintenanceMCP server for local Mac desktop control, enabling mouse, keyboard, and screenshot actions for AI agents like Grok and Cursor.9MIT
TDQS
Scored across 4 tools
Each tool maps to a distinct action on a distinct aspect of the Grok Bot app: enumerating bots, reading a chat, writing to a chat, and clicking a choice option. There is no plausible confusion between read_messages and send_message, and answer_choice is clearly the only tool for responding to multiple-choice prompts.
All four names follow a clean verb_noun snake_case pattern (list_agents, read_messages, send_message, answer_choice). Verb choice is also semantically precise—list vs read vs send vs answer—reinforcing the distinction.
Four tools is a tight, well-scoped surface for driving a single desktop chat app. Each tool covers an indispensable part of the interaction loop (discover, read, write, reply to prompt) with no filler.
The core lifecycle—find the app, read a chat, send a message, answer a prompt—is fully covered with no dead ends. Minor gaps exist around starting a brand-new agent/chat or retrieving fuller conversation history, but agents can work around these via send_message and read_messages.