Use Case
An AgentLed MCP workspace keeps role knowledge, sourcing criteria, candidate enrichment, approvals, outreach, scheduling, and ATS feedback in one loop - so each hiring run learns from the last.
Hiring manager notes, must-have skills, compensation bands, interview feedback, and disqualifiers live across docs, Slack, ATS fields, and memory.
Candidate lists often hide why someone matched, which trade-offs were accepted, and what still needs human review before outreach.
Replies, screen outcomes, interview notes, and offer decisions rarely flow back into sourcing criteria for the next run.
AgentLed MCP turns job specs, manager notes, scorecards, past hires, compensation rules, and disqualifiers into reusable role knowledge.
Agents search LinkedIn, referrals, portfolios, and talent databases with hard filters, nice-to-haves, exclusion rules, and location or availability constraints.
Profiles are enriched with work history, contact paths, public projects, company context, seniority signals, and evidence for each fit or risk call.
OpenClaw and Codex prepare ranked shortlists, outreach angles, and confidence notes so recruiters can approve, edit, or reject candidates before messages send.
Hermes sends approved outreach, routes replies, follows up with context, and books screens against recruiter and interview panel availability.
Every reply, screen result, rejection reason, interview note, and hire outcome updates the ATS and Knowledge Graph so future searches get sharper.
AgentLed MCP
Codex
OpenClaw
Hermes
LinkedIn
Hunter.io
Google Calendar
Slack