"Search for HITL (Human-in-the-Loop or other possible acronyms)" matching MCP servers:

Enables AI assistants to interact with humans through GUI dialogs for text input, choices, confirmations, and information display.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

Enables AI agents to ask human operators questions through polished browser dialogs, supporting text/choice/confirmation inputs and file attachments.

Enables any MCP-capable harness to run queries through a real browser driving real search engines in a configurable fallback chain (Google, DuckDuckGo, Bing, Baidu, Sogou), with CAPTCHA or sign-in handoff, persistent per-engine cookies, and reported provenance for each result.

Enables AI agents to request human decisions and send notifications through chat platforms like Slack and WhatsApp, with ephemeral in-memory pending requests and no central backend.

Bridges Claude Desktop with a HITL escalation service, enabling creation, approval, modification, and management of human-in-the-loop requests directly from the chat interface.

Enforces mandatory human approval before LLM agents can edit files, create files, or execute shell commands, using session tokens and audit logging.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Enables AI assistants to request human input by creating tasks on Amazon Mechanical Turk, integrating human-in-the-loop capabilities via the MCP standard.

Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.

Enables reading, listing, creating, and editing Microsoft Loop pages as Markdown through browser automation.

Enables LLMs to send DM messages to a human via Discord webhook when they need attention — a question, blocker, decision, or completed work — using a standardized, user-controlled format read from a local file or hosted URL.

MCP server that analyzes your writing style to generate personal voice rules, scores drafts for AI slop, and verifies authorship, enabling LLMs to write in your specific voice.

An MCP server that lets users find nearby shops and POIs around a location and find targets such as gas stations or charging points within a given radius along a driving route, using the Amap (Gaode) Web Service API with built-in API key entry and validation.

Routes tasks from AI agents to human workers via webhook providers with smart matching, fallback chains, and proof-of-completion tracking.

Enables coding agents to see the UI they just changed without flooding their context window, returning a structured text summary (console errors, failed requests, overflow, layout shifts, accessibility violations) plus small crops of only the regions that changed since the last capture. All output is fitted into a chosen token budget, with captures stored on disk and evicted automatically.

MCP server for creating and managing digital human models with built-in EU AI Act compliance, part of the MEOK AI Labs ecosystem.

Enables a coding agent to keep one JSON feature specification per feature, governed by a progressive schema, and to render it as editable Markdown documents for a product owner. Answers and direct Markdown edits are reconciled back into the validated model through stdio MCP tools, applying coherent changes and reporting those that widen scope or contradict the model.

A cross-platform MCP server implementing the Ralph Loop iterative development technique where a worker model does the work and a reviewer model provides cross-model review until approval.

Provides a stable, side-effect-free MCP tool contract that enables AI workflows to be prototyped, demoed, tested, or dry-run without connecting to databases, APIs, files, or other real data sources. It enables swapping in a real data server later without changing the AI-facing interface.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

A loop-aware MCP server for your own ComfyUI that enforces a build-run-look-critique-fix cycle, making the model iterate on pixel quality until the output matches the brief.

Local production engineering platform that indexes Python codebases and exposes semantic code analysis, git risk scoring, and log correlation through MCP tools for AI assistants.

Enables AI assistants to store, score, recall, pin, sleep, wake, update, delete, and export memories with importance weighting, type-based decay, emotional valence/arousal, and dormant-memory reactivation through 14 MCP tools.

x402 capability chassis: 170+ AI-callable, pay-per-call data tools (US/global equities, crypto/DeFi, prediction markets, gov/legal, research, infra) settled in USDC on Base mainnet via the Coinbase CDP facilitator. No API keys or accounts — the x402 payment is the auth. Remote MCP at https://the-stall.intuitek.ai/mcp.

Enables AI agents to index, search, and validate lessons learned across project repositories via a local SQLite index, providing learning-loop resources and verified-solution tracking without loading full files into conversations.

MCP server for amazon.in — cheapest in-stock, best-value picks, and price history links.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.