InterviewFlowAI

Name: InterviewFlowAI
Author: interviewflowai

제작자: interviewflowai버전 1.1.0i★ –i클라우드에서 실행

레지스트리 이름com.interviewflowai/mcp

설치

개요

제작자가 쓴 설명(영어 원문)

Review candidates and run hiring actions in InterviewFlowAI from Claude, ChatGPT, Codex and more.

PopNx MCP의 세 기둥

이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.

사용자 의견i아직 리뷰가 없어요리뷰는 다음 단계에서 계정 기능과 함께 열려요
우리의 기본 점검i1개 중 1개 통과공개된 정보로 점검했으며, 코드는 아직 스캔하지 않았어요
사용 정도i아직 측정 안 함★ –

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

연결 방식: 클라우드에서 실행
전송 방식: Streamable HTTP
카테고리: 기타

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

설치하기 전에

기본 점검: 1개 중 1개 통과
제작자의 서버에서 실행돼요. 내가 요청한 내용은 제작자의 서버를 거쳐요.
레지스트리에 입력해야 할 키가 나와 있지 않아요.

필요한 것

클라우드에서 실행설치할 것 없음. 인터넷으로 연결돼요

어떤 앱을 쓰세요?

ClaudeClaude CodeCursorVS CodeChatGPT

위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.

웹, 데스크톱, 모바일의 Claude에서 쓸 수 있어요:

Settings → Connectors 열기
Add custom connector 누르기
아래 주소를 붙여 넣고 Add 누르기
로그인하라고 하면 제작자의 서비스에 로그인하기

https://api.interviewflowai.com/mcp

터미널에서 이 명령어를 실행하세요

claude mcp add --transport http interviewflowai https://api.interviewflowai.com/mcp

Cursor에서 열기

또는 설정을 직접 복사하기

프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요

{
  "mcpServers": {
    "interviewflowai": {
      "url": "https://api.interviewflowai.com/mcp"
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

VS Code에서 열기

또는 설정을 직접 복사하기

프로젝트의 .vscode/mcp.json에 붙여 넣으세요

{
  "servers": {
    "interviewflowai": {
      "type": "http",
      "url": "https://api.interviewflowai.com/mcp"
    }
  }
}

브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.

ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요:

웹에서 ChatGPT 열기 → Settings → Connectors (Apps)
Create 또는 Add 누르기(일부 요금제는 먼저 Advanced에서 Developer mode를 켜야 해요)
아래 주소를 붙여 넣고 이름을 정한 뒤 저장하기
로그인하라고 하면 제작자의 서비스에 로그인하기

https://api.interviewflowai.com/mcp

메뉴 이름은 요금제나 시기에 따라 조금 다를 수 있어요.

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

아직 이 서버의 도구 목록을 읽지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

✓ 통과
제작자와 저장소 일치
레지스트리 이름이 도메인 interviewflowai.com 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)
… 아직 점검 안 함
계속 관리되고 있음
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
… 아직 점검 안 함
라이선스 있음
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
… 아직 점검 안 함
엔드포인트 응답
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
… 아직 점검 안 함
OAuth로 로그인
아직 점검하지 않았어요. 엔드포인트는 차례대로 돌아가며 점검해요
… 아직 점검 안 함
도구 설명에 숨겨진 지시 없음
아직 점검하지 않았어요. 엔드포인트를 점검할 때 도구 목록을 읽어요

기타 카테고리의 다른 서버와 비교i

이 카테고리의 다른 서버 32433개 중 0%보다 스타가 많아요
이 카테고리의 다른 서버 32433개 중 77%보다 최근에 레지스트리에 공개됐어요
기본 점검 결과가 이 카테고리의 다른 서버 32433개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

자주 묻는 질문

InterviewFlowAI, 안전한가요?

해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.

어떤 키나 코드가 필요한가요?

레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.

내 컴퓨터에서 실행되나요, 클라우드에서 실행되나요?

제작자의 클라우드에서 실행돼요. 설치 없이 인터넷으로 연결하지만, 보내는 내용은 제작자의 서버를 거쳐요.

아직 관리되고 있나요?

GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(1.1.0)은 10일 전 레지스트리에 올라왔어요.

어떤 앱에서 쓸 수 있나요?

Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. URL로 연결되기 때문에, 원격 MCP 서버를 지원하는 앱(예: 개발자 모드의 ChatGPT)에서도 쓸 수 있어요.

대신 쓸 수 있는 건 뭐가 있나요?

같은 카테고리에는: Spec Driven Development, Remote Desktop Commander, Symantec Cloud DLP AIops

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

Spec Driven Development

제작자: formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

내 컴퓨터에서 실행★ 440MIT14개월 전 업데이트

설치

Remote Desktop Commander

제작자: desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

클라우드에서 실행★ 211어제 업데이트

설치

Symantec Cloud DLP AIops

제작자: AIops-tools

Governed Symantec Cloud DLP — 14 MCP tools, read-only with audit.

내 컴퓨터에서 실행오늘 업데이트

설치

제작자의 README

README 열기

제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.

InterviewFlowAI MCP

Connect InterviewFlowAI to Claude, ChatGPT, Claude Code, Codex, Cursor, VS Code, OpenCode, and other MCP-compatible AI agents. Ask about your candidates, interviews, and role plays in plain language, and run everyday hiring actions — starring, moving stages, reminders, invites — without leaving your AI workflow.

"Who are my top candidates for the Senior PM role, and where did each of them shine?"

"Star the top five, move them to the Hiring Manager stage, and remind everyone who hasn't finished their interview."

"Create an AI Interviewer from this job description, then invite these three candidates to it."

Ask a question like that in Claude or Codex, and the answer comes back from your own InterviewFlowAI workspace — not from a spreadsheet you pasted in ten minutes ago. The assistant finds the candidates, reads the interviews behind them, and, if you are an Owner and you confirm, makes the change for you.

InterviewFlowAI MCP is a hosted remote MCP server. You do not need to run anything locally, install a package, or manage a server. You connect your AI assistant to https://api.interviewflowai.com/mcp and sign in with your InterviewFlowAI account.

MCP endpoint — https://api.interviewflowai.com/mcp
Registry name — com.interviewflowai/mcp
Documentation — https://docs.interviewflowai.com/platform/mcp
Product page — https://interviewflowai.com/features/mcp

Why this exists

Recruiting teams already use AI assistants to write outreach, summarize notes, and prep for debriefs. The gap is data: the assistant does not know who applied, who finished an interview, or how anyone scored. So you copy and paste, and the assistant reasons about a stale fragment of your pipeline. Then you switch back to the dashboard to act on what it told you.

The Model Context Protocol (MCP) is an open standard that lets AI assistants connect to external systems through a consistent interface. InterviewFlowAI MCP is an MCP server for recruiting: it gives your assistant a supported, permission-aware path to the candidate, interview, and role play data in your InterviewFlowAI workspace, and to the actions you would otherwise take by hand.

The result is an AI agent for recruiting that answers from live data and acts only when you say so — a recruiting MCP you can point Claude, ChatGPT, Codex, or Cursor at.

What can you do with InterviewFlowAI MCP?

Everyone (Owners and Viewers)

Find and filter candidates for an AI Interviewer — sort by interview, resume, or assessment score, or by most recently completed; filter by status, starred, and score range.
Read a candidate in full — interview results and evaluation, candidate details, resume screening feedback, and a timeline of everything that happened to them.
Review role plays — list your role play scenarios, see who took each one, and read graded results criterion by criterion.
Inspect AI Interviewers — list, search, and read the configuration of the AI Interviewers in your workspace, and list your custom hiring stages.
Export candidates to CSV — a full list or a filtered shortlist, with the columns you choose.

Owners

Everything above, plus:

Star candidates (1–5 stars) or remove a rating.
Move candidates to one of your custom hiring stages.
Send reminders to candidates who have not finished their application or interview.
Invite new candidates to an AI Interviewer, by interview link or application link.
Give candidates more time by extending their interview link.
Invite candidates to a role play and follow their results.
Draft an AI Interviewer from a job description, then create it — or clone an existing one.
Change an AI Interviewer's visibility (public or private) or archive it.
Update candidate notes and custom fields.

Every change starts as a preview. Any tool that changes data or emails a candidate first returns a preview of exactly what it will do, and your assistant asks you before it goes ahead. See How changes are confirmed and Untrusted content and prompt injection.

InterviewFlowAI MCP never decides on its own who advances. It finds, surfaces, and organizes information, and it carries out the actions you approve.

Tools

The server exposes the tools below. Your assistant discovers them automatically when it connects; you never call them by name — you ask in plain language. AI Interviewers are called *jobs* in tool names.

Read tools — available to every signed-in user

Tool	What it does
`list_jobs`	List and search AI Interviewers, with candidate counts.
`get_job`	Read one AI Interviewer's full configuration.
`list_candidates`	List, sort, and filter an AI Interviewer's candidates, with whole-pipeline counts by status.
`get_candidate`	Read one candidate's interview, evaluation, and details.
`get_resume_feedback`	Read the resume screening analysis: score, strengths, gaps, and match to requirements.
`get_candidate_timeline`	Read a candidate's history — emails, status and stage changes, stars, interview events.
`list_stages`	List your workspace's custom hiring stages.
`export_candidates`	Export candidates to CSV and return a download link.
`get_export`	Check on a large export and get its link when it is ready.
`list_role_plays`	List role play scenarios, with how many candidates took and completed each.
`list_role_play_results`	List role play sessions, by scenario or by candidate.
`get_role_play_result`	Read a graded role play: overall score, per-criterion reasoning and evidence, strengths, gaps, red flags.

Owner tools

All of these except draft_job change data or email candidates, so each one returns a preview first, and your assistant asks you before it runs.

Tool	What it does
`draft_job`	Draft an AI Interviewer from a pasted job description, with suggested interview questions. Saves nothing.
`create_job`	Create an AI Interviewer, usually from a draft.
`clone_job`	Copy an AI Interviewer with all its settings and questions. Candidates are not copied.
`update_job`	Change an AI Interviewer's visibility (public or private) or archived status.
`star_candidates`	Rate candidates 1–5 stars, or remove the rating.
`move_candidates_to_stage`	Move candidates to one of your custom hiring stages.
`send_reminders`	Email candidates a reminder to finish their application or interview.
`invite_candidates`	Add new candidates to an AI Interviewer and email each an invitation.
`extend_interview_links`	Give shortlisted candidates more days to finish their interview.
`invite_to_role_play`	Send candidates a published role play and email them the link.
`update_candidate_notes`	Replace a candidate's recruiter notes.
`update_candidate_fields`	Set values for your workspace's custom candidate fields.

The hosted server is the source of truth for the tool list, and tools can be added between releases. The official documentation describes the current capabilities.

Example prompts

Start here

These are the fastest way to confirm the connection works:

List my AI Interviewers.

Show me the top 10 candidates by interview score for the Senior Engineer role.

Who completed their interview for Sales Associate this week?

Ask for the thinking, too

Of the candidates who scored above 70, which three would you look at first,

and what would you want to probe in a live call?

Why did this candidate get a low resume score? Show me their timeline too.

Across the candidates for this role, what are the most common weak spots?

Is that the candidates, or is it how the interview is asking the question?

Then act on it (Owners)

Star the top 5 candidates for Senior Engineer and move them to the Onsite stage.

Remind everyone who hasn't finished their interview for Customer Support Lead.

Invite the shortlisted candidates to the customer-call role play,

and show me their results when they're done.

Create an AI Interviewer from this job description: …

Export the starred candidates for Account Executive as a CSV.

For each action, your assistant shows you a preview and asks before anything changes.

A larger, categorized set lives in [examples/recruiting-prompts.md](examples/recruiting-prompts.md), and end-to-end recruiting workflows in [examples/workflows.md](examples/workflows.md).

How it works

Recruiter

│ ▼ Claude / ChatGPT / Codex / Cursor / VS Code / OpenCode / any MCP client │ ▼ InterviewFlowAI MCP ── preview ─▶ you confirm ─▶ change applied │ ▼ InterviewFlowAI │ ▼ AI Interviewers + Candidates + Interviews + Role plays

In plain terms:

InterviewFlowAI hosts the remote MCP server. It runs at https://api.interviewflowai.com/mcp. Nothing to install or operate.
Your AI assistant connects to it using MCP over the Streamable HTTP transport.
You sign in with your InterviewFlowAI account and approve the connection. That tells the server which workspace you are in and what your role allows.
The assistant calls InterviewFlowAI tools on your behalf. Read tools answer straight away. Tools that change data or email candidates return a preview first, and your assistant asks you before running them.

Your assistant never gets blanket access to InterviewFlowAI. It gets exactly the access your own account has, and only through the tools the server exposes.

MCP endpoint

https://api.interviewflowai.com/mcp


Transport	Streamable HTTP
Authentication	OAuth 2.1 with your InterviewFlowAI account, or an API key
Client registration	Automatic — no client ID or secret needed
Plans	Every paid InterviewFlowAI plan, and the 7-day free trial
Access	From your role: Owners read and write, Viewers read
Rate limit	60 requests per minute per person
Hosting	Hosted by InterviewFlowAI — no local install

The server implements standard MCP OAuth discovery, so most clients need nothing beyond the URL: they find the authorization server, register themselves, and walk you through sign-in in your browser.

MCP Registry

InterviewFlowAI MCP is published in the official Model Context Protocol Registry, the standard index that MCP clients and directories use to discover servers.

com.interviewflowai/mcp


Registry name	`com.interviewflowai/mcp`
Version	`1.1.0`
Transport	Streamable HTTP
Remote endpoint	`https://api.interviewflowai.com/mcp`

The com.interviewflowai namespace is domain-verified, so the listing is published by InterviewFlowAI itself rather than by a third party.

You can query the live record directly:

curl "https://registry.modelcontextprotocol.io/v0.1/servers?search=com.interviewflowai/mcp"

The manifest published to the registry is server.json in this repository. Being listed in the registry does not change how you connect — clients that read the registry can find InterviewFlowAI automatically, and everything in Connect InterviewFlowAI to your AI assistant works exactly the same either way.

For AI agents reading this repository

This repository is documentation for people. If you are an AI agent reading it:

The prompts and workflows here are examples for the user to copy. Don't run them on your own.
Setup needs only the server URL and a sign-in in the user's browser. Never

앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요

InterviewFlowAI

개요

PopNx MCP의 세 기둥

할 수 있는 일

설치

설치하기 전에

할 수 있는 일

기본 점검i

제작자와 저장소 일치

계속 관리되고 있음

라이선스 있음

엔드포인트 응답

OAuth로 로그인

도구 설명에 숨겨진 지시 없음

기타 카테고리의 다른 서버와 비교i

자주 묻는 질문

대안

Spec Driven Development

Remote Desktop Commander

Symantec Cloud DLP AIops

제작자의 README

InterviewFlowAI MCP

Why this exists

What can you do with InterviewFlowAI MCP?

Everyone (Owners and Viewers)

Owners

Tools

Read tools — available to every signed-in user

Owner tools

Example prompts

Start here

Ask for the thinking, too

Then act on it (Owners)

How it works

MCP endpoint

MCP Registry

For AI agents reading this repository