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🎯 Hiring Signal MCP — B2B Buying Intent from Career Pages

Detect when companies are actively building teams — and what they're about to buy. Built MCP-first for AI agents (Claude, Cursor, Claude Code).

"A company hiring 1 sales engineer is hiring an SE. A company hiring 5 sales engineers in 60 days is building a sales engineering function — they're about to buy the tools that function needs."

Why this exists

Sales intelligence platforms charge $49–$446/month for hiring/buying-signal data:

For an AI agent making 30 calls/day, this Actor costs ~$9/month vs. a $49+/seat/month subscription.

Built for AI agents (MCP-first)

This is a Model Context Protocol server. Agents connect to it directly — no Apify Console clicks required. Once connected, your agent can call:

• analyze_company_hiring(domain) — full hiring snapshot
• get_buying_signals(domain, role_pattern?, threshold?, window_days?) — detected purchase intent signals
• compare_hiring_velocity(domains[]) — competitive analysis across up to 10 companies

Connect from Claude Desktop or Claude Code

Add to your claude_desktop_config.json (or VS Code MCP config):

{
"mcpServers":{
"hiring-signal":{
"command":"npx",
"args":["-y","mcp-remote","https://YOUR_USERNAME--hiring-signal-mcp.apify.actor/mcp"],
"env":{
"APIFY_TOKEN":"your_apify_api_token"
}
}
}
}

Then ask Claude: "Find the SaaS companies hiring sales engineers in the US right now and rank them by velocity."

How signals are detected (v1: velocity-based)

A buying signal fires when:

• 3+ open roles match the same canonical role
• Posted within 60 days (configurable)
• Recency-weighted, with confidence scoring

Confidence boosts: all-senior matches (+0.10), multi-geography spread (+0.10), 5+ matches (+0.40 cap). Confidence penalties: intern/junior matches (−0.20).

This is intentionally simple, fast, and deterministic — agents don't have to wait for an LLM to decide. Future versions will add pattern-based signals (specific role combinations) and AI-classified intent.

ATS coverage

v0.2 covers ~95% of typical B2B targets across SMB, mid-market, and enterprise. The careers-page fallback catches any company not on a named ATS.

Output schema (truncated example)

{
"domain":"stripe.com",
"company_name":"Stripe",
"total_open_roles":312,
"postings_last_30_days":47,
"postings_last_60_days":89,
"postings_last_90_days":134,
"by_function":{
"engineering":178,
"sales":42,
"product":28,
"ops":19
},
"by_country":{"US":198,"IE":31,"GB":24,"IN":18,"AU":12},
"top_technologies":[
{"technology":"ruby","count":41},
{"technology":"go","count":28}
],
"buying_signals":[
{
"role_pattern":"Sales Engineer",
"matching_roles_count":7,
"window_days":60,
"confidence_score":0.80,
"explanation":"7 open 'Sales Engineer' roles posted in last 60 days across 3 countries — primarily senior+ roles. Pattern suggests active team buildout."
}
]
}

Pricing — Pay-per-event

You pay only for what the Actor delivers.

Worked example. Agent asks: "Compare hiring at Stripe, Notion, and Linear."

• 1 MCP tool call: $0.05
• 3 companies analyzed: $0.60
• ~600 roles extracted: $3.00
• 4 buying signals detected: $0.40
• Total: ~$4.05

Most agent sessions cost $0.30–$2.00 per query.

Use cases

B2B SaaS marketers: Find prospects in active buying mode for your category. "List 50 companies hiring 3+ RevOps roles right now" → instantly actionable target list.

VC analysts: Monitor portfolio company growth. "Compare hiring velocity at all 12 of our Series B portfolio companies" → leading indicator of execution.

Competitive intel teams: Track competitor team buildouts. "Is our top competitor hiring engineers faster than us this quarter?"

Sales leaders: Find net-new accounts your AEs haven't found yet. "Mid-market SaaS companies in NY hiring sales engineers" → instant pipeline.

Why use this over the cheaper alternatives?

Single-platform job scrapers exist on Apify, but they:

1. Target LinkedIn/Indeed (legally fragile, frequently break)
2. Return raw postings — no signal extraction
3. Can't be called from an AI agent
4. Don't aggregate across multiple ATSes

This Actor is MCP-native, signal-extracting, and ATS-agnostic — three things no other Actor on the Store currently combines.

Limitations

• Posted dates are required for velocity signals. Roles without dates are excluded — this prevents false positives from stale postings.
• No LinkedIn scraping, ever. We only use public ATS APIs and career pages. This is the legal moat.
• English-only role classification in v1. Non-English roles are still extracted but not signal-scored.
• Workday discovery requires a link on the company's own careers page. JS-only Workday embeds fall through to the careers-page adapter.

Roadmap

• v0.3: Pattern-based signals (role combinations indicating specific buying intent)
• v0.4: AI-classified buying intent (Gemini reads JDs, infers what tools they're about to buy)
• v0.5: Webhook delivery for "alert when company X starts hiring for Y"

Issues, requests, custom builds

Open an issue on the Actor's Issues tab and we'll respond within 24 hours.