askahuman-mcp
An MCP server that enables AI agents to request human verification for tasks requiring real-world understanding, paying via the Lightning Network, and receiving verified answers.
README
askahuman-mcp
An MCP (Model Context Protocol) server that gives AI agents access to human verification. Ask a human a question, pay via the Lightning Network, and get a verified answer -- all through standard MCP tools.
Any MCP-compatible AI agent (Claude, Gemini, Codex, etc.) can use this server to request human judgment on tasks that require real-world understanding, common sense, or subjective evaluation.
Platform launch coming soon — The AskAHuman marketplace is on its way. Follow @AskAHumanOnline for updates.
Prerequisites
- Node.js >= 18
- LND node with REST API enabled and a funded channel (for Lightning payments)
Installation
Run directly (no install required):
npx askahuman-mcp
Or install globally:
npm install -g askahuman-mcp
Configuration
All configuration is via environment variables:
| Variable | Required | Description |
|---|---|---|
ASKAHUMAN_API_URL |
Yes | Base URL of the AskAHuman API (e.g. https://api.askahuman.online) |
LND_REST_URL |
Yes | URL of your LND node's REST API (e.g. https://localhost:8080) |
LND_MACAROON_HEX |
Yes | Hex-encoded LND admin macaroon for payment authorization |
LND_TLS_CERT_PATH |
No | Path to LND's TLS certificate file (required for self-signed certs) |
LOG_LEVEL |
No | Log verbosity: debug, info, warn, error (default: info) |
Copy .env.example to .env and fill in your values:
cp .env.example .env
Tools
The server exposes five tools to AI agents:
| Tool | Description | Key Inputs |
|---|---|---|
ask_human |
Submit a question and pay via Lightning. Returns immediately with a verificationId (status PENDING) -- poll check_verification for the answer |
question, taskType, context?, choices?, images?, urgent?, callbackUrl?, maxBudgetSats?, maxWaitMinutes? |
check_verification |
Poll the status of a verification; returns terminal + nextStep so the agent knows when to stop |
verificationId |
cancel_verification |
Check refund eligibility (advisory, no state change) | verificationId |
request_refund |
Claim a refund for an expired-unclaimed task | verificationId |
get_pricing |
Query current server-side pricing | taskType? |
Task types
BINARY_DECISION-- Yes/No questionsMULTIPLE_CHOICE-- Choose from provided options (supplychoices[])TEXT_RESPONSE-- Free-form text answerMEDIA_VERIFICATION-- Verify one or more images and get a free-form text answer (supplyimages[]as public https URLs, max 8;choices[]is not allowed for this type)
Quick start
Claude Desktop
Add to your Claude Desktop MCP configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"askahuman": {
"command": "npx",
"args": ["askahuman-mcp"],
"env": {
"ASKAHUMAN_API_URL": "https://api.askahuman.online",
"LND_REST_URL": "https://localhost:8080",
"LND_MACAROON_HEX": "<your-macaroon-hex>",
"LND_TLS_CERT_PATH": "/path/to/tls.cert"
}
}
}
}
Restart Claude Desktop. The ask_human tool will be available in your conversations.
Example usage
ask_human is non-blocking: it prices the task, pays the Lightning invoice, submits the request, and returns right away with a verificationId and status: "PENDING". The agent then polls check_verification until the human responds. (The MCP request timeout is far shorter than a human's response time, so the tool never blocks waiting for an answer.)
Text / decision task — the agent is prompted:
"Ask a human whether this email looks like a phishing attempt: [email content]"
ask_humanreturns immediately:{ "status": "PENDING", "verificationId": "vid-123", "amountPaidSats": 50 }- The agent polls
check_verification({ "verificationId": "vid-123" })every 30–60s:- While
terminal: false(nextStep: "keep_polling") → keep polling. - When
terminal: truewith statusCOMPLETED→ the human's answer is in theresultfield.
- While
Image task (MEDIA_VERIFICATION) — verify images and get a free-form answer:
ask_human({
"taskType": "MEDIA_VERIFICATION",
"question": "Do both photos show the same person?",
"images": [
"https://example.com/a.jpg",
"https://example.com/b.jpg"
],
"maxWaitMinutes": 240
})
// → { "status": "PENDING", "verificationId": "vid-456", "amountPaidSats": 80 }
Image URLs must be public https links (up to 8). Then poll check_verification exactly as above.
Multiple choice — supply choices[]:
ask_human({
"taskType": "MULTIPLE_CHOICE",
"question": "Which category best fits this support ticket?",
"choices": ["Billing", "Bug report", "Feature request", "Spam"]
})
If a task expires in the queue without being claimed, check_verification returns nextStep: "call_request_refund" — call request_refund({ "verificationId": "..." }) to reclaim the sats.
Development
# Clone the repository
git clone https://github.com/AskAHumanOnline/askahuman-mcp-server.git
cd askahuman-mcp-server
# Install dependencies
npm install
# Build
npm run build
# Run tests
npm test
# Run with coverage
npx jest --config jest.config.cjs --coverage
# Lint
npm run lint
# Start the server (stdio transport)
npm start
# Interactive tool testing with MCP Inspector
npx @modelcontextprotocol/inspector dist/index.js
Running tests
Unit tests mock all external I/O (HTTP calls, LND). No running services are required.
npm test
Integration tests (in tests/integration/) are skipped by default. They require:
- A running AskAHuman backend
- A Polar Lightning Network with funded channels
How it works
The server implements the L402 payment protocol:
- Submit -- The agent sends a verification request to the AskAHuman API
- Pay -- The API returns a 402 with a Lightning invoice; the MCP server pays it via the agent's LND node
- Authenticate -- The payment preimage proves payment; the server retries with L402 credentials
- Return -- The request is queued for a human verifier and
ask_humanreturns immediately with averificationId(statusPENDING) - Poll -- The agent calls
check_verificationevery 30–60s until it returnsterminal: true; statusCOMPLETEDcarries the human's answer inresult
If a task expires without being claimed, check_verification signals nextStep: "call_request_refund" and the agent can call request_refund to reclaim the sats.
License
MIT
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