How do I get an API key?
Sign up at humanrail.dev to get your API key. Use `ek_live_...` for production or `ek_test_...` for testing.
Humanrail MCP Server
@prime001
Basic information
About Humanrail MCP Server
MCP server for HumanRail — route tasks requiring human judgment to vetted workers from any AI agent
Humanrail MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"humanrail": {
"command": "uvx",
"args": [
"humanrail-mcp-server"
],
"env": {
"HUMANRAIL_API_KEY": "your-api-key"
}
}
}
}Humanrail MCP Server tools
7Route a task to a human worker for review/judgment
Check the status and result of a task
Poll until a task completes (blocking)
Cancel a pending task
List tasks with filters (status, type, date range)
View usage stats and billing summary
Check if the HumanRail API is reachable
Overview
What is Humanrail?
Humanrail is an MCP server that routes tasks requiring human judgment from any AI agent to a vetted worker pool. It verifies results, pays workers via Lightning Network, and returns structured output — acting as a “Stripe for human judgment.”
How to use Humanrail?
Install with pip install humanrail-mcp-server or run directly with uvx humanrail-mcp-server. Configure your API key in the environment variable HUMANRAIL_API_KEY (get one at humanrail.dev) and add the server to your Claude Code or Claude Desktop config. Once connected, your AI agent can use tools like create_task, get_task, and wait_for_task to route and retrieve human‑reviewed results.
Key features of Humanrail
- Routes tasks to a curated human worker pool
- Pays workers instantly via Lightning Network
- 6‑stage verification pipeline validates every result
- Define expected output with JSON Schema
- Pay‑per‑task pricing with no subscriptions
- Supports custom task types and common use cases
Use cases of Humanrail
- Content moderation: determining if content is appropriate
- Refund eligibility: deciding whether to approve a refund
- Data verification: confirming the accuracy of information
- Quality assessment: rating an output on a numeric scale
- Document review: extracting or verifying information from documents
- Sentiment analysis: identifying the tone or intent of a message
Frequently asked questions
What are the pricing tiers?
Pricing is per task, with no subscription. Low‑risk tasks cost $0.10–$0.50, medium‑risk $0.25–$1.00, and high/critical tasks $1.00–$5.00, depending on complexity, SLA, and risk tier.
What task types can I create?
You can create any custom task type. Common examples include `content_moderation`, `refund_eligibility`, `data_verification`, `quality_assessment`, `document_review`, and `sentiment_analysis`.
Can I define the expected output format?
Yes. Use JSON Schema in the task to specify the exact fields and types you need back (e.g., a boolean for approval or a score with a reason).
How does the verification process work?
The process consists of six steps: create (send the task with context and schema), route (assign the best‑matched worker), execute (worker reviews and submits judgment), verify (a 6‑stage pipeline checks the result), pay (worker is paid via Lightning Network), and return (result is available via `get_task` or `wait_for_task`).
More Other MCP servers
FastMCP v2 🚀
jlowin🚀 The fast, Pythonic way to build MCP servers and clients.
26.0K
Activepieces
activepiecesAI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
23.2K
Lemon.io
lemon-ioRequest dedicated senior developers to work on your project, write job descriptions, and prep technical interviews — all without leaving your Claude chat. Just describe what you need, and Lemon.io MCP does the rest. 1–3
🚀 Model Context Protocol (MCP) Curriculum for Beginners
microsoftThis open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
16.7K
Yuppsy
Yuppsy MCP: build and publish real estate websites from your AI assistant. Yuppsy lets your AI assistant create live websites for real estate agents and individual property listings. You don't need a designer or any code
Comments