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Manage recruiting workflows in natural language, from screening to scored interview reports.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "AI Interview Agents MCP Server" yet — see the docs or source repo.
Create a role for a Senior Frontend Engineer requiring 5+ years of React and TypeScript experience and working-level English. Then screen the 20 resumes I uploaded, rank candidates by fit, and explain each person's strengths and weaknesses.
Returns the role details, a ranked candidate shortlist, and screening rationale for each resume.
Select the top 5 shortlisted candidates and schedule 45-minute first-round interviews, preferably next Tuesday to Thursday afternoons. If there are conflicts with interviewer or candidate availability, suggest alternatives and update interview statuses automatically.
Generates interview schedules, conflict-resolution suggestions, and updated interview statuses.
Read the scored reports and transcripts for all completed interviews. Summarize each candidate's scores in technical ability, communication, and role fit, then provide a final recommendation list and rejection reasons.
Outputs a candidate score summary, interview highlights, and final hiring recommendations with rejection notes.
Search AI-native jobs, prepare applications, and practice interviews efficiently.
Explore a developer’s profile, skills, and projects via natural language.
Manage job application materials, fetch job postings, and prepare for interviews.
Calculate weighted candidate-job fit scores from skills and role requirements.
Turn CVs and projects into MCP tools for querying and job matching.
Load job descriptions, analyze fit, and tailor resumes for specific roles.