"A simple test or quiz" matching MCP servers:

Enables coding agents to query the dependency graph of a GitHub backlog, retrieve ordered ready work and prerequisite chains, atomically claim issues, and report blockers—so agents work in the correct order and safely in parallel.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

A foundation for creating custom Model Context Protocol servers that can integrate with AI systems, providing a simple BMI calculator tool as an example implementation.

A simple MCP server combining FastMCP and LangGraph that enables AI agent interactions through tools for asking questions to an OpenAI-powered agent and receiving personalized greetings.

Exposes AI agents as MCP tools to fetch Jira stories, generate BRDs and Playwright test scripts, run tests, and auto-heal broken locators. Integrates with Claude Desktop and Cursor IDE for enterprise-grade test automation.

Pay-per-call USDC payment proxy for AI agents. Issue scoped Pay Tokens with hard spending caps and auto-journal every charge to freee / Money Forward / QuickBooks.

Gives LLMs a genuine in-game seat in Civilization V, letting them scout, settle, negotiate, fight, and manage a civilization through tool calls with the same fog-of-war information a human player sees.

Simple sequential thinking MCP in python

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

Cybersecurity AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

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.

Industry 4.0 / IIoT AI agents for manufacturing: explain OEE losses per shift, triage machine alarms, find downtime root causes, prepare predictive-maintenance jobs and write shift reports from Unified Namespace (UNS), MQTT or historian data. Plus an industrial AI-readiness diagnostic and a vendor-neutral digital-transformation advisor. Works in Claude Code, Codex and any MCP client.

Transforms HTML into Figma designs using only the user’s design system, ensuring correct component usage or safe fallback to primitives, while continuously learning from each build to improve mapping accuracy and consistency.

AgentPay — x402 crypto data gateway on Stellar. 10 live pay-per-call tools: token prices, whale activity, gas tracker, DeFi TVL, Fear & Greed, Dune queries, token security. Agents pay USDC on Stellar. No API keys. Budget-aware sessions.

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

Enables AI agents to participate in meetings by pulling pending requests, reading context, and submitting answers through a Supabase-based MCP server.

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.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

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.

Mandatory human approval gate for autonomous AI agents. Before any critical, irreversible, or financially significant action executes — file deletion, production deployment, financial transaction — the agent calls oracle_validate. A human receives a real-time Telegram notification with full context and taps Approve or Reject. The agent waits for the decision before proceeding.

Enables collaboration across Claude, GPT, and Gemini through a unified MCP interface, with configurable execution policies for synthesizing or directly delivering worker outputs.

Provides a human-approval tool for MCP-compatible agents, pausing execution until a human approves or edits the action, with every decision logged.

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.

Enforces structured adversarial reasoning via devil's advocate, premortem, assumption audit, and steelman protocols to stress-test claims and decisions.

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.

Enables a host AI agent to trigger a multi-agent debate, running N-rounds where agents critique each other's answers, then synthesizes a consensus recommendation with ranked options.

Lets MCP clients submit a situation and typed questions (yes/no, choice, or scale) to a decision model that returns calibrated probabilities plus an act-or-escalate flag. Enables agents to route, flag, approve, check, or rate cases and hand uncertain ones to a person.

MCP server that lets coding agents test AI agents. Create YAML test cases, snapshot golden baselines, check for regressions, and generate visual reports all from inside Claude Code or any MCP-compatible tool. Works with LangGraph, CrewAI, OpenAI, Claude, Mistral, and any HTTP API.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

Lets separate coding-agent sessions coordinate through a shared, role-addressed mailbox instead of a human relaying every message, over a single local SQLite file or a hosted server with many isolated channels. Messages can be sent as tracked obligations that stay open until one side resolves and the other confirms, alongside threads, full-text search, work statuses, and an append-only versioned pin system where protected changes require recorded agreement from every declared role.

MCP OpenVision is a Model Context Protocol (MCP) server that provides image analysis capabilities powered by OpenRouter vision models. It enables AI assistants to analyze images via a simple interface within the MCP ecosystem.

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

Ask Vulnify before an AI agent acts: get ALLOW, REVIEW or BLOCK, and read and test policies.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.

Password AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables AI coding agents from any vendor to resume a task from the exact stopping point without model calls, re-reading old sessions, or re-exploring the code, by merging host hooks, agent checkpoints, and Git deltas into one compact brief. It also guards credits outside the model with a prompt clarity gate, a loop guard, and configurable token profiles.

Enables agents to start and check monotonic elapsed-time timers so they can verify whether a user-requested minimum task duration has been met, including during tool waits.

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.