Spec Driven Development
de formulahendry
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar
InterviewFlowAI
Resumen
Descripción del creador (original en inglés)
Review candidates and run hiring actions in InterviewFlowAI from Claude, ChatGPT, Codex and more.
Los tres pilares de PopNx MCP
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
- Opinión de usuariosiAún no hay reseñasLas reseñas se abrirán junto con las cuentas en una etapa posterior
- Nuestras revisiones básicasi1 de 1 superadasRevisado con información pública; el código aún no se ha escaneado
- UsoiAún sin medir★ –
Qué puedes hacer con él
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
- Conexión: Se ejecuta en la nube
- Transporte: Streamable HTTP
- Categoría: Otros
Instalación
Elige la app de IA que usas y copia la configuración.
Antes de instalar
- Revisiones básicas: 1 de 1 superadas
- Se ejecuta en el servidor del creador: lo que le pidas pasa por su servidor.
- El registro no indica ninguna clave que completar.
Necesitas
- Se ejecuta en la nubeNo hay nada que instalar; se conecta por internet
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Funciona en Claude para web, escritorio y móvil:
- Abre Settings → Connectors
- Presiona Add custom connector
- Pega la dirección de abajo y presiona Add
- Si te pide iniciar sesión, inicia sesión en el servicio del creador
https://api.interviewflowai.com/mcpEjecuta esto en tu terminal
claude mcp add --transport http interviewflowai https://api.interviewflowai.com/mcpO copia la configuración tú
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"interviewflowai": {
"url": "https://api.interviewflowai.com/mcp"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
O copia la configuración tú
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"interviewflowai": {
"type": "http",
"url": "https://api.interviewflowai.com/mcp"
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
ChatGPT solo se conecta a servidores en internet:
- Abre ChatGPT en la web → Settings → Connectors (Apps)
- Presiona Create o Add (en algunos planes primero hay que activar Developer mode en Advanced)
- Pega la dirección de abajo, ponle un nombre y guarda
- Si te pide iniciar sesión, inicia sesión en el servicio del creador
https://api.interviewflowai.com/mcpLos nombres de los menús pueden variar un poco según el plan y con el tiempo.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Qué puede hacer
Todavía no hemos leído la lista de herramientas de este servidor; revisamos los endpoints por turnos.
Revisiones básicasi
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
- ✓ Superada
El creador coincide con el repo
El nombre en el registro se verificó con el dominio interviewflowai.com (el registro comprueba quién es dueño del dominio)
- … Aún sin revisar
Sigue en mantenimiento
Todavía no hemos leído este repo en GitHub
- … Aún sin revisar
Tiene licencia
Todavía no hemos leído este repo en GitHub
- … Aún sin revisar
El endpoint responde
Aún sin revisar; revisamos los endpoints por turnos
- … Aún sin revisar
Inicio de sesión con OAuth
Aún sin revisar; revisamos los endpoints por turnos
- … Aún sin revisar
Sin instrucciones ocultas en las descripciones de herramientas
Aún sin revisar; leemos la lista de herramientas cuando revisamos el endpoint
Comparado con otros en Otrosi
- Más estrellas que el 0% de los otros 32375 servidores de esta categoría
- Publicado en el registro más recientemente que el 77% de los otros 32375 servidores de esta categoría
- Revisiones básicas iguales o mejores que el 100% de los otros 32375 servidores de esta categoría
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Preguntas frecuentes
¿Es seguro InterviewFlowAI?
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
¿Qué claves o códigos necesita?
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
¿Se ejecuta en mi computadora o en la nube?
Se ejecuta en la nube del creador. Te conectas por internet sin instalar nada, pero lo que envías pasa por los servidores del creador.
¿Sigue en mantenimiento?
El repo de GitHub cambió por última vez –, y la última versión (1.1.0) llegó al registro hace 10 días.
¿Qué apps pueden usarlo?
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. Se conecta por URL, así que también funcionan las apps que aceptan servidores MCP remotos, como ChatGPT en modo desarrollador.
¿Qué puedo usar en su lugar?
En la misma categoría: Spec Driven Development, Remote Desktop Commander, DiffCI
Alternativas
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Remote Desktop Commander
de desktop-commander
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Se ejecuta en la nube★ 211Actualizado ayer
Instalar
DiffCI
de DiffCI
Fail-closed, change-aware verification for AI coding agents with affected-test guidance.
Computadora o nubeActualizado hoy
Instalar
README del creador
Abrir el README
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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/mcpand 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
Solo se muestra el principio; lee el resto en el repo