"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 stdio MCP server that lets Claude Code delegate coding tasks to an OpenCode instance (optionally attached to an internal LLM gateway), with follow-up replies, status polling, output/diff retrieval, cancellation, and cleanup handled in a single session. It supports managed or attach modes, sandbox and approval policies, parallel fan-out delegations, and read-only review workflows.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

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

Enables MCP clients to delegate routine coding tasks to a local model in isolated git worktrees, using test results as a gate and the client as the reviewer before changes are merged.

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 Codex to delegate review and implementation tasks to the local Qoder CN CLI as background jobs, with two permission tiers and polling-based status updates.

The IDE for agents — read by symbol, edit against a revision, validate with your own build, revert. It is a local stdio MCP server for coding agents. It reads code by symbol with tree-sitter and real language servers (Go, Java, Scala, TypeScript, Python, Rust, Ruby), edits against a known revision and returns compiler diagnostics with each edit, runs the repository's own build, test etc.

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.

Enables AI coding agents to compile, test, run, hot-swap, and debug Java applications incrementally through MCP, providing runtime feedback for verifying code changes.

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.

Enables primary AI orchestrators to delegate token-heavy coding tasks to economical models via OpenRouter, running sandboxed autonomous ReAct loops with filesystem operations and git audit tools while reducing token costs.

Exposes the local Claude Code CLI as a subagent for Codex, enabling background review and implementation jobs with two fixed permission tiers.

Stop treating AI like a chatbot. Turn ChatGPT into a team of AI agents that can plan, code, test, and review your local projects. ccc-mcp brings multi-agent workflows, evidence-based reviews, and cross-chat task recovery to your own codebase.

Enables a two-model AI coding workflow inside Claude Code, where one model plans and reviews while a second model writes code, with test verification, automatic rollback, and learned improvements.

Enables AI agents to delegate complex coding tasks, refactorings, and automated code reviews to OpenAI Codex and Google Antigravity CLIs, running them autonomously in YOLO mode with process supervision.

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

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.

Three.js MCP server and Claude Code plugin: screenshot, play, test and profile the three.js pages your coding agent builds, in headless Chrome or Firefox.

Enables coding agents to inspect and mutate code in zero-copy RAM shadow workspaces, explore competing fixes in parallel, and commit only syntax- and test-validated changes to disk through a compact MCP tool surface.

Autonomous coding pipeline exposed as an MCP server: plan, dispatch, review, and merge software stories through worktree-isolated agents. A frontier model (Claude) handles judgment — planning, review, risk adjudication — while a local model does the implementation, gated by TDD and a merge-time test rerun on the rebased branch.

Ask other AI models (GPT, Claude, Gemini, Grok and more) from the app you already use, one by name or several at once. Every answer says what paid for it: your API keys, your ChatGPT plan, or free requests.

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

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.

Enables developers to delegate asynchronous coding tasks to a cloud-based autonomous agent, creating tasks, reviewing and approving execution plans, sending feedback, monitoring sessions, and retrieving diffs and Pull Requests directly from an MCP-compatible IDE. It also supports configurable mock mode for local testing without consuming API credits.

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.

Delegates test writing to a headless second coding agent in an isolated git worktree, then builds, runs the tests, verifies that only test paths changed, and returns a compact report plus optionally applies the verified tests to your checkout. It also flags failures that point to bugs in the production code rather than the tests, keeping test code and terminal logs out of the main agent's context.

Enables AI coding agents to review Swift code, scaffold new iOS apps, and build, test, and preview them in the Xcode Simulator using local Apple guides and source references.

Lets AI coding agents ask a Rails app about itself: 35 read-only tools answer from the schema, models, routes, controllers, views, jobs and conventions, over MCP or the command line, even when the app cannot boot.

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.

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.

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.

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.

Enables Claude Code to delegate tasks such as planning, coding, reviews, debugging, tests, and docs to a cheaper model that works autonomously in a project-sandboxed loop with file, search, and test tools, returning a compact report to save tokens. Routing rules, approval-gated deletes and commands, per-task model/effort settings, and backups keep the user in control of what gets handed off.

Enables Codex to delegate coding tasks to a locally hosted Qwen model through an MCP tool, which can read, write, patch, test, and inspect git diffs inside an allowed workspace.

Enables MCP-compatible AI clients like Claude Code, Cursor, and Codex to invoke Google Antigravity's Gemini coding agent for repository-aware file operations, command execution, code review, test generation, and quota checks, while also providing a standalone dual-mode CLI.