The AI-native interface to your Revenue Operating System.
Artefact Revenue Intelligence MCP Server
The AI-native interface to your Revenue Operating System. Version-controlled GTM intelligence — signals, commits, and closed-loop measurement — accessible to any AI agent.
A Model Context Protocol (MCP) server that treats your Go-to-Market strategy like code: versioned, diffable, and deployable. Detect pipeline signals, identify scaling constraints, analyze value engines, and draft structured GTM changes — all through AI-native tool calls. Built on the Artefact Formula methodology from real B2B consulting engagements.
Why Artefact MCP?
Traditional ICP models stop at firmographics. We triangulate across three dimensions to identify prospects with the right profile, the right behaviors, AND the right trajectory.
| Feature | HubSpot Official MCP | Generic Wrappers | Artefact MCP |
|---|---|---|---|
| CRUD operations | Yes | Yes | Via HubSpot API |
| RFM Analysis | No | No | 11-segment classification |
| ICP Triangulation | No | No | Firmographic + Behavioral + Growth Signals |
| Pipeline Health | No | No | 0-100 health score + exit criteria testing |
| Signal Detection | No | No | 6-type signal taxonomy |
| Constraint Analysis | No | No | Dominant bottleneck + Revenue Formula |
| Value Engine Analysis | No | No | Growth / Fulfillment / Innovation |
| GTM Commit Drafting | No | No | Structured change proposals with evidence |
| Methodology built-in | No | No | Artefact Formula (10 resources) |
| Works without API key | No | No | Yes (demo data) |
Who Is This For?
- B2B revenue teams using HubSpot who want AI-powered signal detection and pipeline intelligence
- RevOps managers who need constraint analysis and value engine health accessible from Claude or Cursor
- Consultants who deliver RFM analysis, ICP scoring, and evidence-backed GTM recommendations to clients
- Developers building revenue intelligence integrations with MCP
- AI agents that need a structured interface to reason about and propose changes to GTM strategy
Tools
Signal Intelligence
`detect_signals` — Pipeline Signal Detection
Scans pipeline data for all 6 signal types from the Artefact signal taxonomy: velocity anomalies, conversion drop-offs, win/loss patterns, pipeline concentration, data quality issues, and SPICED frequency signals. Returns structured signal objects with strength scores (0-1), evidence, and recommended actions.
`identify_constraint` — Dominant Constraint Analysis
Identifies which of the 4 scaling constraints (Lead Generation, Conversion, Delivery, Profitability) is bottlenecking revenue. Includes Revenue Formula breakdown (Traffic x CR1 x CR2 x CR3 x ACV) with gap-to-benchmark analysis and recommended focus.
`analyze_engine` — Value Engine Health
Analyzes health of the 3 value engines: Growth (create/capture/convert demand), Fulfillment (onboard/deliver/renew/expand), and Innovation (gather/prioritize/build/launch). Returns engine-specific metrics, health scores, and integrated signal detection.
`propose_gtm_change` — GTM Commit Drafting
Enables AI agents to propose structured GTM changes following the commit anatomy: Intent, Diff, Impact Surface, Risk Level, Evidence, and Measurement Plan. Supports 8 entity types (ICP, persona, positioning, pipeline stage, exit criteria, GTM motion, scoring model, playbook).
Analysis Tools
`run_rfm` — RFM Analysis
Scores clients on Recency, Frequency, and Monetary value. Segments them into 11 categories (Champions through Lost) and extracts ICP patterns from top performers. Now includes signal framing — detects win/loss patterns, revenue concentration, and at-risk client signals. Supports B2B service, SaaS, and manufacturing presets.
`qualify` — ICP Triangulation Framework
Scores prospects across three dimensions: Firmographic Fit (industry, revenue, employees, geography), Behavioral Fit (tech stack, engagement, purchase history), and Growth Signals (hiring, funding, expansion). Now includes constraint context — maps prospect fit to your dominant scaling constraint. Returns tier classification (Ideal / Strong / Moderate / Poor) with engagement strategy.
`score_pipeline_health` — Pipeline Health Score
Analyzes open deals for velocity metrics, stage-to-stage conversion rates, bottleneck identification, and at-risk deal detection. Now supports optional exit criteria testing (pass/fail per criterion per deal) and includes signal framing for velocity anomalies and conver
Tools (7)
detect_signalsScans pipeline data for 6 signal types including velocity anomalies and conversion drop-offs.identify_constraintIdentifies scaling bottlenecks using the Revenue Formula breakdown.analyze_engineAnalyzes health of Growth, Fulfillment, and Innovation value engines.propose_gtm_changeDrafts structured GTM changes with evidence and impact analysis.run_rfmScores clients on Recency, Frequency, and Monetary value with 11-segment classification.qualifyScores prospects using firmographic, behavioral, and growth signal triangulation.score_pipeline_healthAnalyzes open deals for velocity, conversion rates, and bottleneck identification.Environment Variables
HUBSPOT_API_KEYAPI key for HubSpot integrationConfiguration
{"mcpServers": {"artefact": {"command": "uvx", "args": ["artefact-mcp"]}}}