Mav MCP. Automate Candidate Screening Via SMS Campaigns

Mav connects your AI client straight into a recruiting pipeline, letting you handle candidate screening and lead qualification using SMS conversations. You don't have to touch an inbox; your agent manages it all for you.

To get started, you can use create_lead. Running this tool both creates the new candidate record in the system and immediately kicks off an automated screening playbook designed just for them.

When you need to check up on a specific person, you've got get_lead. It pulls every current detail for a single lead ID, giving you their qualification score and full status report. You can also use list_leads; this shows you every candidate in the entire system, along with basic metrics like what stage they're at right now.

Want to see exactly what kind of automated workflows are available? Use list_playbooks to display all the screening playbooks Mav has built out. If you need to know how a specific playbook works, you run get_playbook. This pulls the full structure and ruleset for any given automation.

For keeping track of everything that's happening—the replies received or when a campaign finishes—you use list_activities. It gives you a chronological list of every recent event across your entire account. You can also check what campaigns are running by using the playbook tools to manage outbound SMS outreach, letting you launch and monitor large-scale recruiting efforts targeting lists of candidates.

Managing an active lead means controlling the automation. You can use update_lead to change specific data points on an existing record, like their salary expectations or when they're available for interviews. If a candidate needs manual eyes on them before the playbook continues, you run stop_playbook. This stops any ongoing automated screening process for that lead so you can step in.

Sometimes a lead isn't ready for outreach. You can use opt_out_lead to manually remove a candidate from all future SMS communications and campaigns, keeping the pipeline clean. The system also gives you direct control over playbooks; besides stopping them, your agent handles the whole sequence of automated conversations.

Here's how it works: Your AI client talks directly to these tools. By calling create_lead, you initiate an automatic screening conversation flow with a target prospect. If you need deep background data on one candidate, calling get_lead pulls all current details, including their history and status. You use the list functions—list_leads, list_playbooks, and list_activities—to audit your entire operation.

To manage the content of those conversations, you can update lead data with update_lead. When a playbook needs to pause for human review, you run stop_playbook. You're never stuck in an inbox because every action—from creating the initial record via create_lead to opting someone out using opt_out_lead—is handled through these specific tools.