Artefact Revenue Intelligence
by alexboissAVcommunityv0.3.3
Artefact Revenue Intelligence MCP Server is a Model Context Protocol server that enables AI-driven analysis and management of Go-to-Market strategies, providing insights into pipeline signals, scaling constraints, and value engines.
From the registry: Revenue intelligence MCP: RFM analysis, 14.5-point ICP scoring, pipeline health. HubSpot.
Install & configure
Prerequisites
- requiredInstall artefact-mcpInstall via pip or uvx
$ pip install artefact-mcp
Install in your client
Paste into the AI you're chatting with — it will figure out the rest
Please install the `artefact-revenue-intelligence` MCP server into my current AI client (that's you).
Required prerequisites (do these first if not already done):
- **Install artefact-mcp** — Install via pip or uvx Run: `pip install artefact-mcp`
Canonical MCP server config (stdio transport):
- command: `python3`
- args: ["-m","artefact_mcp"]
- optional environment variables:
- `HUBSPOT_API_KEY`: HubSpot private app token (optional; tools work with source='sample' without it) (example: `pat-na1-xxxxxxxx`)
- `ARTEFACT_LICENSE_KEY`: License key for Pro/Enterprise tier
- `ARTEFACT_PROPERTY_MAPPING_PATH`: Path to JSON file with custom HubSpot property mappings (Pro/Enterprise) (example: `/path/to/artefact_property_mapping.json`)
- `ARTEFACT_RFM_THRESHOLDS_PATH`: Path to JSON file with custom RFM scoring thresholds (Pro/Enterprise) (example: `/path/to/rfm_thresholds.json`)
Note: Python method recommended over uvx to avoid PATH issues. Free tier works without HubSpot API key via source='sample'.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.Note: Python method recommended over uvx to avoid PATH issues. Free tier works without HubSpot API key via source='sample'.
Tools (7)
detect_signals
Scans pipeline data for various signal types and returns structured signal objects.
identify_constraint
Identifies the dominant scaling constraint affecting revenue.
analyze_engine
Analyzes the health of value engines related to Growth, Fulfillment, and Innovation.
propose_gtm_change
Enables AI agents to propose structured changes to the Go-to-Market strategy.
run_rfm
Scores clients based on Recency, Frequency, and Monetary value.
qualify
Scores prospects based on firmographic, behavioral, and growth signal dimensions.
score_pipeline_health
Analyzes open deals for velocity metrics and identifies bottlenecks.
Environment variables
HUBSPOT_API_KEYrequiredAPI key for accessing HubSpot data.Prerequisites
- • python3
Packages
artefact-mcp
pypiv0.3.3transport: stdio
Details
- Language
- Python
- License
- NOASSERTION
- Released
- Feb 13, 2026
- Last commit
- May 23, 2026
- Registry name
- io.github.alexboissAV/artefact-revenue-intelligence