"小红书 MCP 服务器 - Related Information or Services" matching MCP servers:

Simple sequential thinking MCP in python

Enables AI coding agents like Claude Code or Codex to delegate tasks to a DeepSeek Harness subagent with its own context window, providing tools for task delegation, result waiting, continuation, and supervision with sandboxed execution.

Wraps the local Qoder CLI into an MCP server, enabling any MCP client to delegate coding tasks to a local Qoder agent with session management, sandboxed permissions, and model selection.

A minimal local MCP server that lets Claude Desktop or Claude Code delegate coding tasks to Grok Build running headless as a subagent.

This MCP server is designed for planning with Claude Code, Cline, or Cursor and making changes with Cerebras to maximize speed and intelligence while avoiding API limits. It uses the Qwen 3 Coder model for high-quality code generation and can be embedded in IDEs.

MCP server that runs JetBrains' ReSharper command-line tools for code inspection and cleanup, exposed to C# coding agents over stdio.

Provides per-Subagent MCP controls to any coding agent or client across all your MCPs and prevents context window waste. Loads only 3 tools instead of all your MCP Server's tool definitions. Agents discover tools on-demand, only when needed and only the servers and tools they are allowed.

Resilient multi-CLI orchestration server for AI agents that routes tasks to Claude, Gemini, or Codex with automatic retry, circuit breaker, and fallback.

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.

Enables coding agents to connect to Debug Adapter Protocol debuggers over MCP, allowing them to launch or attach to native targets, control execution, set breakpoints and watchpoints, inspect stacks, variables, memory, and exceptions, and capture agent-friendly debugger snapshots.

Enables external agents to list T3 environments and projects, start coding threads, monitor progress, send follow-up instructions, and interrupt running turns via MCP.

Enables parallel execution of shell commands and AI coding agents (Claude, Gemini, Codex) across lists of items like files or URLs, with batched processing and real-time streaming output for batch operations.

Enables coding agents to search and retrieve persistent repository memory created by Cliper, providing context, gaps, architecture, and timeline information via MCP tools.

Enables AI assistants and MCP clients to launch and manage Cursor Cloud Agents on repositories or without one, select models, follow up mid-run, retrieve or cancel results, and check usage and cost.

Enables Claude Code and OpenAI Codex to ask each other questions through iTerm panes, with no daemon or per-project configuration.

Connects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.

MCP server that lets any agent or MCP host delegate tasks to Claude Code running headless, with tools for review, validation, analysis, and autonomous work.

MCP server for Google Jules enabling LLMs to create coding sessions with automatic pull request creation from issues or custom prompts.

MCP server that lets any agent or MCP host delegate tasks to the Cursor CLI agent for fast, headless execution. Supports task delegation, project discovery, file analysis, and follow-up sessions.