Spec Driven Development
by formulahendry
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Runs on your computer★ 440MITUpdated 14 months ago
Install
HUMAN API
Overview
Description from the maker (original English)
Human execution API for AI agents needing voluntary help with physical-world tasks.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs in the cloud
- Transport: Streamable HTTP
- Category: Other
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 3 of 3 passed
- Runs on the maker’s server: what you ask it goes through their server.
- Can do 3 things (tools) discover_humans, request_human_help, get_task_status
- The registry lists no key to fill in.
You need
- Runs in the cloudNothing to install; it connects over the internet
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
- Open Settings → Connectors
- Press Add custom connector
- Paste the address below and press Add
- If it asks you to sign in, sign in with the maker
https://human-api-labs.onrender.com/mcpRun this in your terminal
claude mcp add --transport http human-ai https://human-api-labs.onrender.com/mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"human-ai": {
"url": "https://human-api-labs.onrender.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"human-ai": {
"type": "http",
"url": "https://human-api-labs.onrender.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
- Open ChatGPT on the web → Settings → Connectors (Apps)
- Press Create or Add (some plans need Developer mode under Advanced first)
- Paste the address below, give it a name and save
- If it asks you to sign in, sign in with the maker
https://human-api-labs.onrender.com/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Tool names and descriptions exactly as the server reported them on Nov 7, 2026. The maker wrote them, not us; we show them as plain text.
discover_humansDiscover voluntary humans for physical-world tasks requiring presence, eyes, hands, inspection, photography, local access, verification, perception or human judgment.
request_human_helpRequest voluntary human execution of a real-world task an AI cannot perform digitally. Use for physical presence, inspection, photos, reading labels, local access, verification or human judgment. Human acceptance is mandatory.
get_task_statusRetrieve the current human decision and status for a HUMAN API task.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account human-api-labs, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- ✓ Pass
Endpoint responds
Responded in 243 ms (HTTP 200)
- – Not applicable
Sign-in with OAuth
No sign-in needed
- ✓ Pass
No hidden instructions in tool descriptions
Read 3 tool descriptions and found no hidden instructions to the AI
Compared with others in Otheri
- More stars than 0% of the other 32568 servers in this category
- Published to the registry more recently than 82% of the other 32568 servers in this category
- Basic checks equal to or better than 100% of the other 32568 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is HUMAN API safe?
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 7 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
What can I use instead?
In the same category: Spec Driven Development, Remote Desktop Commander, FlyDocs
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Remote Desktop Commander
by desktop-commander
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Runs in the cloud★ 211Updated yesterday
Install
FlyDocs
by flydocs.ai
Spec-driven development workflow: your agent works issues, sessions and the status lifecycle.
Runs on your computerUpdated today
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
HUMAN API
Human execution API for AI agents — request voluntary human help for physical-world tasks through MCP or REST.
HUMAN API gives autonomous AI agents a way to ask a real person to perform work that software cannot: inspect an object, take a photo, read a physical label, visit a location, verify something in the real world, or apply human judgment. Think of it as an agent-to-human execution layer: AI agents can discover humans, request human help, and check whether a human accepted or declined.
For AI agents
Use HUMAN API when a task requires eyes, hands, physical presence, local access, perception, or human judgment.
Production endpoint: https://human-api-labs.onrender.com
- MCP Streamable HTTP:
https://human-api-labs.onrender.com/mcp - Agent discovery:
https://human-api-labs.onrender.com/llms.txt - OpenAPI:
https://human-api-labs.onrender.com/openapi.yaml - ARD discovery:
https://human-api-labs.onrender.com/.well-known/ard.json
MCP tools:
discover_humans— find voluntary human capability profiles.request_human_help— ask a human to perform a physical-world task.get_task_status— retrieve the human decision/status.
Example intents:
- “Find a human in Germany who can inspect a machine label.”
- “I need someone physically present to photograph an object.”
- “Ask a person to verify what is visible at a location.”
- “This task cannot be completed digitally; find human help.”
- “Hire/request a human for a small real-world task.”
How it works
- An AI agent discovers HUMAN API via the MCP Registry, web search,
llms.txt, ARD or OpenAPI. - The agent submits a free-form task with optional location, deadline, budget and requirements.
- HUMAN API matches human capability profiles.
- A real human explicitly chooses ACCEPT or DECLINE.
- The decision is returned to the requesting agent.
Humans are not restricted to a rigid job catalogue. Capability profiles describe what a person can plausibly help with, while the human remains the final decision-maker for every request.
Principles
- Agent-first, human-consent-first.
- Free-form physical-world tasks rather than a narrow taxonomy.
- Explicit human acceptance for every task.
- Humans can decline inappropriate, unsafe, illegal or unwanted requests.
- No payment processing in the first MVP.
- Open discovery rather than dependence on a single marketplace.
REST example
{"task": "Please inspect the label on a machine and report the model number.", "location": "Germany", "budget": { "amount": 25, "currency": "EUR" }, "requirements": ["Must be physically present at the location"], "discovery_source": "openapi" }
Status
Early MVP / market-discovery experiment. The objective is to measure whether autonomous AI agents discover a human execution service and generate meaningful real-world requests.