Official MCP server for AI Interview Agents — run the hiring workflow (roles, CV screening, interview scheduling, scored reports) from any MCP client.
AI Interview Agents — MCP Server
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
The official Model Context Protocol server for AI Interview Agents, a voice-AI hiring platform. It lets any MCP client (Claude, Cursor, custom agents) drive the recruiting workflow in natural language: create roles, screen CVs, schedule and manage candidate interviews, and read back scored reports with transcripts.
The live voice interview itself is out of scope here (that runs on a separate real-time service). This server *triggers* interviews and *reads back* the results.
What it exposes
- **Roles** — list your roles, or create one from a job description.
- **Candidates & CVs** — parse dropped CV/PDF files, normalize messy pasted candidate lists (names, emails, phone numbers, experience, skills), and reassign candidates between roles.
- **Interviews** — schedule interviews (with a dry_run mode that normalizes and previews without sending anything or consuming quota), reschedule, cancel, and send reminders.
- **Reports** — read the candidate pipeline and pull back scored interview reports with transcripts.
Use the hosted server (recommended)
The server runs remotely with OAuth sign-in. Point any Streamable-HTTP MCP client at:
Your client discovers the auth flow automatically via /.well-known/oauth-protected-resource and signs you in with your AI Interview Agents account. It is also listed in the official MCP Registry as com.aiinterviewagents/interviews.
Run it locally (stdio)
AIIA_BACKEND_URL overrides the API base if you are pointing at your own deployment.
How auth works
The server holds no account secrets. Each request carries the user's own Firebase ID token, forwarded to the backend as a bearer token — the same trust path as the web app. For the hosted transport, an OAuth layer (dynamic client registration + PKCE) bridges MCP clients to Firebase sign-in.