Coresignal

@Coresignal find senior machine learning engineers at Series B startups in San Francisco who joined in the last 6 months

The fast search returned 47 matching employee profiles. The results include ML engineers and research scientists at companies like Anthropic, Scale AI, and Cohere who started between October 2024 and March 2025. Each preview record shows current title, company, start date, and LinkedIn profile URL. For example: Sarah Chen, Senior ML Engineer at Anthropic (started Jan 2025); Marcus Liu, Research Scientist at Scale AI (started Nov 2024). This is an illustrative snapshot—actual results depend on Coresignal's index coverage at query time.

This example uses the Fast Search tool, which is lower-cost and ideal for straightforward queries. The MCP translates natural language into an Elasticsearch query behind the scenes. Note that preview records are summaries; you'll need separate API calls to fetch full profiles. Results reflect Coresignal's B2B data index, which may not capture every startup or recent hire.

@Coresignal get the real-time profile for employee ID cs_emp_12847563, and make sure the data is no older than 1 hour

Retrieved current profile for Jane Rodriguez (max_age=1). She is now VP of Engineering at DataCo (promoted from Director in February 2025). Her profile includes 8 years of experience, skills in distributed systems and Kubernetes, education from MIT, and links to 3 recent conference talks. The response confirms this data was refreshed 23 minutes ago, so it meets the 1-hour freshness requirement. This illustrative example shows the structure—actual profiles vary by individual and data availability.

This example demonstrates the Get Real-Time Employee Profile tool, which requires a separate Real-time Employee API entitlement from Coresignal. Setting max_age=0 or a low value forces a fresh fetch, which may incur higher costs or rate limits. Use this when you need up-to-the-minute accuracy (recent job changes, new skills) rather than cached data.

@Coresignal search for companies hiring aggressively in cybersecurity roles, then summarize which ones have the most open positions and fastest growth in headcount

The reasoning search identified 12 companies with 10+ open cybersecurity roles and >30% YoY headcount growth. Top three: CrowdStrike (34 open roles, 42% growth), Wiz (28 roles, 61% growth), and Snyk (19 roles, 38% growth). The MCP explained it filtered for 'security engineer,' 'SOC analyst,' and related titles, then cross-referenced employee growth data. It noted ambiguity around 'aggressive hiring'—clarified as both volume and velocity. This is an illustrative synthesis; actual company counts and growth rates depend on Coresignal's dataset at the time of query.

This example uses Search With Reasoning, the higher-cost mode that interprets ambiguous queries and can ask for clarification. It consumed ~100 trial credits in this illustrative run (query-mode call). Use this when you need the AI to explain its logic or when Fast Search returns unclear results. The synthesis step—ranking by headcount growth—happens in the AI layer, not the MCP itself.

When Coresignal beats LinkedIn for candidate context at scale

A 6-person recruiting team at a Series A SaaS company needs to build lists of 200+ senior engineers at competitor companies every quarter, then enrich each profile before outreach. Coresignal's Fast Search tool pulls job titles, company tenure, and skills in bulk without hitting LinkedIn's rate limits or requiring individual seat licenses. The trade-off: profiles lag real-time by days or weeks, so if someone just changed jobs, you'll miss it unless you pay for the real-time entitlement and set max_age=0. If your outreach cadence is weekly or slower and you're sourcing at volume, Coresignal gives you the data moat LinkedIn won't sell you directly.

Building competitor headcount models without manual scraping

A 3-person market research team at a PE firm tracks hiring velocity and org structure at 40 portfolio competitors each month. Coresignal's employee search returns department size, title distribution, and growth trends across all 40 targets in one query, then exports to a shared spreadsheet for the investment committee. The reasoning tool clarifies ambiguous searches like 'engineering leadership' versus 'technical program managers' when job titles vary by company. The limit: if you need real-time alerts the day a VP of Sales joins a competitor, Coresignal's cache delay means you'll hear about it 24-72 hours late. For monthly or quarterly reporting where patterns matter more than individual moves, this MCP turns weeks of LinkedIn stalking into 20 minutes of structured queries.

When to use Coresignal for enterprise account mapping

A 10-person sales team at a B2B security vendor needs to map decision-makers at 50 enterprise accounts before a quarterly business review cycle. Coresignal's company and employee search pulls reporting lines, recent hires in IT and procurement, and tenure data to identify who's new versus entrenched. The API key setup means the whole team shares one entitlement without per-seat CRM integration costs. The catch: if your deal cycle is under 30 days or you're selling into fast-moving startups where roles change weekly, the profile lag kills urgency. If you're running 90-day enterprise cycles and need a snapshot of who's who before the first call, Coresignal gives you the org chart your AE won't build manually.