humanforai
OfficialThis server lets AI agents hire a real human operator to perform real-world tasks requiring physical presence, human perception, or judgment. All services are currently free during the pilot phase, with communication via email.
get_human_services: Retrieve the full catalog of available services, operator profile (location, languages, working hours), response times, and trust & safety policy.submit_human_task: Submit a task and receive atask_idfor tracking. Supported task types include:Real-world verification, product/app testing, human judgment & feedback
Data collection, local physical-world tasks, AI output review
Prompt & workflow testing, simulation & automation testing
Accessibility/usability checks, custom human-in-the-loop tasks
Options for deadline, output format (text report, structured JSON, annotated screenshots, video), location, and contact email for deliverable delivery.
check_task_status: Poll a task's progress bytask_idthrough stages: submitted → under_review → accepted → in_progress → delivered (or rejected), with operator notes.message_human_operator: Send free-form messages to scope work, ask questions, or discuss custom projects before formal submission — requires areply_toemail for operator responses.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@humanforai Verify the price of milk at the local grocery store."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
humanforai
MCP server for Human For AI — a human endpoint for AI agents. Let your AI agent hire a real human operator for tasks that need physical presence, human perception, or human judgment:
Real-world verification — confirm a place, product, price, or claim exists, with photo/text evidence
Product or app testing — a real human installs, uses, and reports
Human judgment and feedback — tone, clarity, trustworthiness, design quality
AI output review — human review before your output reaches production
Data collection — gathering/labeling that needs human perception or local access
Local physical-world tasks — visit, photograph, check, measure, observe
…and more — call
get_human_servicesfor the full catalog
All services are free during the proof-of-concept pilot. No API key, no payment. Every task is reviewed by the human operator before acceptance; illegal, harmful, deceptive, unsafe, or privacy-invasive tasks are rejected. First response within 12 hours, any day of the week — typically much faster: the operator is push-notified the moment a task arrives.
Tools
Tool | Purpose |
| Service catalog, accepted task types, limits |
| Submit a task; returns a |
| Poll a submitted task by |
| Ask questions / scope work before submitting |
Status transparency
check_task_status shows progress in real time, not just the final result:
seen_by_operator_at— the moment a human actually saw the task (usually well before the first status change)eta— operator-set delivery estimate, added when the task is acceptedstatus_history— every transition (submitted → accepted → delivered, orrejected) with timestamps
Related MCP server: ProofStream MCP Server
Setup
Claude Code
claude mcp add human-for-ai -- npx -y humanforaiClaude Desktop / other MCP clients (stdio)
{
"mcpServers": {
"human-for-ai": {
"command": "npx",
"args": ["-y", "humanforai"]
}
}
}Clients with native remote MCP support
You don't need this package — connect directly to the hosted endpoint (streamable HTTP, no auth):
https://humanforai.dev/mcpE.g. Claude (Settings → Connectors → Add custom connector), or:
claude mcp add --transport http human-for-ai https://humanforai.dev/mcpHow it works
This package is a thin stdio proxy to the hosted Human For AI MCP endpoint. Tool definitions come from the live server, so they are always current — the package itself has no logic to go stale.
Previously published as human-api, which still works but is deprecated in favor of this package.
Typical flow
get_human_services— see what the operator can dosubmit_human_task— be specific and self-contained; includecontact_emailto receive the deliverablecheck_task_status— poll with the returnedtask_id
Links
Website: https://humanforai.dev
API docs: https://humanforai.dev/api
Machine-readable manifest: https://humanforai.dev/.well-known/agent.json
OpenAPI spec: https://humanforai.dev/openapi.json
Trust & safety: https://humanforai.dev/trust
License
MIT
Available Tools
4 toolscheck_task_statusCheck task statusARead-onlyInspect
Look up a submitted task by its task_id. Returns current status (submitted → under_review → accepted → in_progress → delivered, or rejected), status history with timestamps, and any operator notes.
Inputs: task_id (required).
get_human_servicesList human servicesARead-onlyInspect
Fetch the Human For AI manifest: available services, operator profile (location, languages, working hours), response times, accepted and rejected task types, and trust & safety policy. Call this first to decide whether and how to hire the human. The catalog is examples, not limits — unlisted needs are welcome as custom_human_in_the_loop.
Inputs: no named parameters.
message_human_operatorMessage the human operatorAInspect
Send a free-form message to the human operator — questions, scoping, custom or recurring projects, anything that is not yet a ready-made task. Include reply_to (an email you or your principal can read); it is the only way the operator can answer.
Inputs: message (required), from, subject, reply_to.
submit_human_taskSubmit a task to the humanAInspect
Submit a task for the human operator to perform in the real world. Returns a task_id immediately; the human reviews every task before accepting it (this is not instant execution). Free during the pilot. Include contact_email — it is how the deliverable reaches you.
Inputs: task_type (required), description (required), deadline, requester, +4 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool serves a distinct purpose: checking task status, fetching service manifest, messaging the operator, and submitting tasks. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern using underscores (check_task_status, get_human_services, etc.), making them predictable and easy to differentiate.
With 4 tools, the server is well-scoped for its human-in-the-loop purpose—covering information retrieval, communication, task submission, and status tracking—without excess or deficiency.
The tool surface covers core interactions (info, messaging, submit, status), but lacks a cancel/modify task capability, which could be needed for real-world tasks.
Maintenance
Related MCP Connectors
Hire humans for physical-world tasks from your AI agent: missions, claims, proof, KYC status.
Hire a real person for your AI agent: real-world tasks done with photo or video proof.
Hire a verified local human for small real-world tasks your AI agent can't do.
Human-as-a-Service for AI agents. Delegate tasks that need a real human, get results via API.
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