"B&R Automation" 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.

Enables ChatGPT to schedule future proactive messages and receive queued events into conversations through MCP Apps, without calling the OpenAI API.

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.

An AI personality collaboration tool based on Model Context Protocol (MCP) that enables users to summon and collaborate with multiple AI personas for intelligent analysis and problem-solving.

缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台，致力于通过代理AI技术减少人力成本，高效高精度为用户提供分钟级接入的内容风控解决方案，破解安全威胁，提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel

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

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.

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.

OS keychain secrets for AI coding agents, over MCP. Anchors credentials to the native vault (macOS Keychain, Linux Secret Service, Windows Credential Vault) and exposes them through 44 policy-governed tools: per-environment values, TTL, linked rotation, encrypted transfer bundles, redacted exec, and a tamper-evident audit log. Local-first, no cloud account.

Enables MCP clients to evaluate spend gates and manage human-in-the-loop approvals for CHP Profile B.

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.

Windows desktop automation MCP server enabling screenshot capture, precise visual locating of UI elements via vision models, and automated mouse clicking.

A persistent, self-revising hypothesis DAG for agentic R&D, exposed as an MCP server. It enables agents to structure working knowledge as a directed acyclic graph of hypotheses, with automatic write-back belief revision and cascading pruning based on evidence.

Enables git-branch-style A/B experimentation for long-running tasks, allowing users to create, compare, promote, discard, or roll back parallel conversation branches via MCP tools.

It enables AI agents to recover from failures by diagnosing issues, refocusing broad tasks, restoring session context, and managing retries safely with bounded memory and credential redaction.

Enables AI agents to interact with X (Twitter) through its private GraphQL API using session cookies, supporting tweets, replies, likes, retweets, searches, direct messages, and more. Provides 24 MCP tools for full account automation.

MCP Server for OpenTTT — Proof of Time tools for AI agents AI Agent A and Agent B both trigger a payment at the same time. Who was first? OpenTTT answers this with cryptographic Proof of Time — synthesized from multiple independent time sources, verified through GRG integrity shards, and signed with Ed25519 for non-repudiation.

MCP server for AI browser automation with tools for navigation, actions, data extraction, and scripting, supporting local and cloud execution.

Empower LLMs with fine-grained visual understanding — detect, localize, and describe anything in images with natural language prompts.

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