# B2B Buyer-Signal MCP

**Intent layer for AI sales agents — structured signal interpretation, not data scraping.**

Built from 10+ years of B2B enterprise sales experience.

> **Disclaimer.** Outputs are structured signal-interpretation frameworks based on publicly-documented B2B sales practice. Not investment, financial, or legal advice. Not a substitute for human qualification. Verify any specific claim about a company, person, or event with primary sources before outreach.

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## Why This Exists

Every AI SDR and sales agent today has the same structural gap: they have signal data (from Apollo, Clay, Crunchbase, scrapers, paid APIs) but no consistent interpretation layer. They know a target hired a Head of Sales, but they don't know what to do with that information.

This MCP bridges that gap. **Provide a signal payload — receive structured outreach implications.**

It does NOT scrape data sources. Use Apify / Clay / Apollo / Crunchbase / LinkedIn ecosystem for upstream collection. This MCP is the interpretation engine.

## 6 Tools

| Tool | What it returns |
|---|---|
| `interpret_hiring_signal` | Signal strength, outreach timing, pitch angle, pitfalls, decision window for hiring events (new exec, team expansion) |
| `interpret_funding_signal` | Same for funding events (seed → IPO, down rounds) including budget bands and typical buyers |
| `interpret_tech_stack_change` | Same for tech-stack changes (added/removed competitor, warehouse adoption, compliance tooling) |
| `interpret_leadership_change` | Same for C-suite changes (CEO/CFO/CTO/CMO/founder departures) |
| `interpret_expansion_signal` | Same for market expansion (international office, vertical, product launch) |
| `score_buyer_intent` | Composite intent score (0-100) given multiple signals — for prioritization |

## Sample Use

```typescript
// AI agent observes: "Acme just hired a new Head of Sales last week + announced Series B"
// Calls:
mcp.call("interpret_hiring_signal", { signal_type: "head_of_sales" });
mcp.call("interpret_funding_signal", { funding_stage: "series_b" });
mcp.call("score_buyer_intent", { signals: ["head_of_sales", "series_b"] });

// Returns: tier, recommended action, pitch angle, decision window
```

## Pricing

- Apify Pay-Per-Event: **$0.05 per tool call**
- First 10 calls free per actor

## Production Roadmap

This v1.0 is the **interpretation layer**. Future versions:

- v1.1: Multi-signal correlation patterns (e.g., "head_of_sales + sdr_team_expansion within 30 days = pre-Series-A signal")
- v1.2: Industry-specific weightings (SaaS vs Fintech vs Healthcare have different signal half-lives)
- v1.3: Time-decay scoring (signal age affects weight)
- v2.0: Optional bring-your-own-data adapter for Clay / Apify Scrapers / Crunchbase API

## Built By

[Elisabeth Hitz](https://www.linkedin.com/in/elisabethhitz) — 10+ years of B2B enterprise sales experience across ad-tech, SaaS, media, and global hiring. Five-year stretch overshooting quota at a publicly-listed ad-tech company. Now building MCP servers for the AI agent ecosystem.

License: MIT