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SeekOut MCP can search five specialized talent pools and, when connected for your organization, your ATS pipeline. The available results depend on your SeekOut permissions and the data sources enabled for your account.

Choose a data source

Your assistant can infer a suitable source from the role and context in your request. Name a source when you need precise control or want to compare results across pools.

Search the GitHub talent pool for Rust engineers in Berlin with recent open-source contributions.

Available talent pools

Your ATS pipeline

If your organization has a connected ATS, you can search existing applicants and candidates by role, stage, application date, recruiter notes, and other available pipeline fields. This helps you check internal talent before starting a new external search.

Find previous applicants for data engineering roles who reached an interview stage but were not hired.

ATS availability and searchable fields depend on your organization’s integration and your SeekOut permissions.

Search guidance by source

  • Public profiles: Start with the role, location, seniority, and must-have skills. Add company or industry constraints only when they matter.
  • GitHub: Name the relevant languages or technologies and ask for contribution evidence rather than relying only on self-reported skills.
  • Academic & Expert: Specify the research area and use publication, citation, patent, or h-index criteria when relevant.
  • Healthcare: Use the clinical specialty or subspecialty, location, and hospital affiliation. Include license requirements when they affect eligibility.
  • Nursing: State the nurse type, specialty, license state, and location. Distinguish between credentials such as RN, LPN, NP, and APRN when needed.
  • ATS pipeline: Include the role, stage, date range, or disposition you want to review.

Search across sources

Ask for a combined view when a role may appear in more than one pool. Your assistant can return a unified result or help you compare sources separately.

Show me the talent landscape for machine learning researchers in Boston across public profiles, Academic & Expert, and GitHub. Explain which source each candidate came from.

Continue with Recruiting workflows, or see Prompting tips for ways to refine a search.