"A simple test or quiz" matching MCP servers:

Simple sequential thinking MCP in python

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

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

A secure, containerized workspace for LLMs to autonomously code, test, and debug projects without risking the host machine.

An MCP server that lets Claude Code delegate coding tasks such as code generation, review, refactoring, and test writing to a local Ollama instance running a Qwen3 model.

Enables Claude Code to delegate bounded repository tasks to DeepSeek as a local sub-agent, handling exploration, routine changes, and test runs within a controlled workspace and budget.

An MCP server that enables local AI models to receive guidance from remote 'senior' AI providers like OpenAI, Anthropic, and Gemini to solve programming problems. It features intelligent multi-turn dialogue management, context synchronization, and automated session history tracking.

A safe, local MCP server that lets Claude drive a controlled software-development loop (inspect, read, plan, patch, apply, check, analyze, fix, summarize) on a project, using deterministic tools and real diffs/test runs.

Provides coding agents with repository context through tools that generate AGENTS.md files or structured JSON summaries, quoting build/test commands from the repo's manifests for a small fee without an API key.

Enables a supervisor LLM to delegate coding tasks to a persistent OpenCode server, block until the turn completes or needs input, and resume the same turn with answers or permission decisions.

Delegates work from MCP clients (like Claude Code) to the Codex CLI, allowing spawning of autonomous Codex subagents for tasks.

Enables running multiple AI CLI tools (Claude, Codex, Gemini, Forge, OpenCode) as background processes with automatic permission handling, allowing LLMs to execute async multitasking and combine different AI models.

An MCP server that enables AI clients to autonomously discover, analyze, fix, test, submit, and track open-source contributions on GitHub through specialized tools.

Agentic MCP server that receives a feature specification from an IDE, autonomously implements it in an isolated sandbox via an internal loop (plan-act-validate-correct), and returns a structured report with diffs and test results, without modifying the original repository.

An MCP server that enforces hard quality gates on AI coding agents, including forced web search, planning, and empirical test execution, to prevent common failure modes and ensure production-grade code.

Bridges a main agent (e.g., Codex) to a separate execution model in Claude Code Haha Desktop, enabling delegated coding tasks with file modifications, test runs, and change auditing.

Enables orchestration of multiple Claude Code sessions for complex multi-task coding projects with HEAD/SUB coordination and dependency-based task execution.

MCP server that enables Claude Code to delegate tasks to DeepSeek and other LLMs, offering 20 tools for code review, analysis, testing, and code generation.

A guarded Model Context Protocol server that lets AI assistants inspect, edit, test, and validate explicitly approved local software projects, featuring 49 focused MCP tools for project discovery, safe editing, Git inspection, Laravel integration testing, and more.

Bridges Claude Code CLI with Cursor IDE to use your existing Claude subscription without separate API costs.