#loop

Route tasks requiring human judgment to a vetted worker pool from any AI agent. Content moderation, refund decisions, data verification, quality assessments — when AI hits its limit, HumanRail routes to humans, verifies results, and pays workers via Lightning Network. 7 tools: create_task, get_task, wait_for_task, cancel_task, list_tasks, get_usage, health_check.

Stateless circuit breaker that detects recursive agent loops in MCP tool calls. Uses Bloom filter to identify repeated calls within 30 seconds. Pay $0.005 USDC via x402 on Base network to reset context and break the loop.

Human-in-the-loop API for autonomous AI agents. When your agent hits a CAPTCHA, needs KYC verification, a phone call, or any task requiring human judgment, SiliconBridge connects it to a real human operator. 22+ services starting at $1, with L402 payments, Stripe, and crypto support.

Human-in-the-loop API for AI agents. When your agent hits a CAPTCHA, 2FA prompt, identity check, or any human-only gate — SiliconBridge routes it to a real human operator who solves it in under 60 seconds. Result returned via API or webhook. Python SDK available: pip install siliconbridge

Structural observability for AI conversations and financial risk management. 17-channel pattern detection, loop/convergence/scattering detection, and OHLCV risk overlay with 31/31 validated drawdown reduction.

Agentwork solves your tasks with humans-in-the-loop

A Model Context Protocol (MCP) server implementing the Dual-Cycle Metacognitive Reasoning Framework for autonomous agents. This tool empowers agents with greater self-awareness and reliability through intelligent loop detection and experience acquisition.

Trigger a help request directly from your IDE via MCP and get human help in minutes

A Model Context Protocol (MCP) server implementation that exposes Pearl's AI and Expert services through a standardized interface

Intelligent Model Context Protocol (MCP) server for AI-assisted API development. Generate mock servers from OpenAPI specs with advanced logging, performance analytics, and server discovery. Optimized for AI development workflows with comprehensive testing insights and automated analysis.

MockLoop MCP is a powerful tool that helps developers create mock API servers effortlessly. 🚀 With just a few commands, you can set up a testing environment that mimics your production API. 💻

pydantic-ai-researcher is a research system that orchestrates an asynchronous loop between two specialized agents: a research agent and an evaluator agent. The research agent answers complex queries using external MCP servers, while the evaluator agent assesses and refines these answers, iterating until a satisfactory response is attained.

A simple chat loop that includes multple mcp servers.