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., "@Pingfusi Is my pricing page confusing anywhere?"
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.
pingfusi is an MCP that lets AI agents call human reviewers.
Think MTurk for AI agents. With pingfusi your agent can:
Get a second opinion: a real person looks at the work, not another model
Get human judgment: where opinion is the answer — design taste, wording, which version people prefer
Skip the iteration loop: the agent revises, another human checks each round, and you only see the finished version
Related MCP server: Pingfusi
Set up Pingfusi for your coding agents with a single command.
npx pingfusi setupHere are some example prompts you can try with the pingfusi MCP.
feedback about | example prompt | what you get | demo |
a confusing page |
| comments pinned to what's off | |
a website clone |
| a perfectly cloned website | |
design taste |
| design feedback | |
video vibes |
| feedback pinned to timestamps |
Each of these publishes the work first so the reviewer can open it; when in doubt, publish: a reviewer can only judge what they can see. Text-only questions work too — if words can carry the whole question, the reviewer just sees the question.
Two lifetime reviews are free. The paid plan includes 100 Pingfusi credits for $30/month, with no rollover. Game playtesting is available through Qaping, with its own credits; it is not a Pingfusi review job.
Every job is the same loop underneath:
File a review — the agent pushes the work (a built site, a video, any artifact) so the reviewer can open it, then files a review with concrete steps to check and what counts as approval.
A human reviews — a real person opens the work and sends back pinned comments anchored to the exact elements that are off.
You get better output — the reviewer's comments land in the agent's context, so the next version is shaped by real human feedback.
Example: you ask for a landing page that doesn't look like AI slop. The agent publishes it, a reviewer answers "gradient looks template-y" and "too much padding under the hero". The agent fixes both and refiles; the next reviewer approves. You come back to a page a human signed off on.
The full command lives in docs/COMMANDS.md.
pingfusi setup install + onboarding
pingfusi doctor check the install; prints a fix per problem
pingfusi ask "<question>" ask a human reviewer, from any directory
pingfusi studio [ping_id] local viewer for review results —
sessions, recordings, transcripts, key moments,
agent findings (contract: docs/STUDIO.md)MIT
This server cannot be deployed
Human-in-the-loop for AI coding agents — ask questions, get approvals via Slack.
Versioned artifact review for people and AI agents, with contextual comments and human control.
Coordination hub for AI coding agents: message teammates, ask humans, audit every event.
Give any AI agent a way to ask a person — for approval, a decision, an answer or a review.
