Revenue intelligence MCP: RFM analysis, 14.5-point ICP scoring, pipeline health. HubSpot.
Revenue intelligence MCP: RFM analysis, 14.5-point ICP scoring, pipeline health. HubSpot.
Is it safe?
No known CVEs for @smithery/cli.
No authentication — any process on your machine can connect to this server.
License not specified.
Last scanned 0 days ago.
Is it maintained?
Commit history unknown.
Will it work with my client?
Transport: stdio, http. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
How much context will it use?
7 tools. Estimated ~900 tokens of your context window (0.4% of 200K).
What if it doesn't work?
Common issues: JSON syntax errors in config, wrong Node.js version, npx cache, network or firewall blocking. covers troubleshooting.
{
"mcpServers": {
"artefact-revenue": {
"env": {
"HUBSPOT_API_KEY": "pat-na1-xxxxxxxx"
},
"args": [
"-m",
"artefact_mcp"
],
"command": "python3"
}
}
}Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
npx -y @smithery/cli 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
detect_signalsPipeline 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_constraintDominant 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_engineValue 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_changeGTM 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).
run_rfmRFM Analysis - Scores clients on Recency, Frequency, and Monetary value. Segments them into 11 categories (Champions through Lost) and extracts ICP patterns from top performers. Includes signal framing — detects win/loss patterns, revenue concentration, and at-risk client signals. Supports B2B service, SaaS, and manufacturing presets.
qualifyICP 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). Includes constraint context mapping prospect fit to dominant scaling constraint. Returns tier classification (Ideal / Strong / Moderate / Poor) with engagement strategy.
score_pipeline_healthPipeline Health Score - Analyzes open deals for velocity metrics, stage-to-stage conversion rates, bottleneck identification, and at-risk deal detection. Supports optional exit criteria testing (pass/fail per criterion per deal) and includes signal framing for velocity anomalies and conversion drop-offs. Returns a 0-100 health score.
scoring-modelICP Triangulation Framework technical reference
methodology://scoring-model
tier-definitions4-tier classification system
methodology://tier-definitions
rfm-segments11 RFM segment definitions with scoring scales
methodology://rfm-segments
spiced-frameworkSPICED discovery framework
methodology://spiced-framework
data-requirementsHubSpot data setup and enrichment requirements
methodology://data-requirements
value-engines3 value engine definitions (Growth, Fulfillment, Innovation) with stages and metrics
methodology://value-engines
exit-criteriaStandard pipeline exit criteria per stage with proof requirements
methodology://exit-criteria
constraints4 scaling constraints with diagnostic criteria and remediation levers
methodology://constraints
signal-taxonomy6 signal types with detection methods and action mappings
methodology://signal-taxonomy
revenue-formulaRevenue Formula breakdown: Traffic x CR1 x CR2 x CR3 x ACV x (1/Churn)
methodology://revenue-formula
gtm-commit-anatomy5 components of a structured GTM commit (intent, diff, impact, risk, evidence)
methodology://gtm-commit-anatomy
Last scanned 5h ago
No known vulnerabilities.
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