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fastmcp-me

Artefact Revenue Intelligence MCP Server

by fastmcp-me
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tasks
{
  "list": {},
  "cancel": {},
  "requests": {
    "tools": {
      "call": {}
    },
    "prompts": {
      "get": {}
    },
    "resources": {
      "read": {}
    }
  }
}
tools
{
  "listChanged": true
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
run_rfmA

Run RFM (Recency, Frequency, Monetary) analysis on client data.

Scores clients based on purchase behavior, segments them into 11 categories, and extracts ICP patterns from top performers.

Args: source: Data source — "auto" (uses HubSpot if API key is set, otherwise sample data), "hubspot" for live HubSpot data, "sample" for built-in demo data. industry_preset: Scoring preset — "b2b_service", "saas", "manufacturing", or "default".

Returns: JSON with scored clients, segment distribution, ICP patterns, and tier recommendations.

qualifyA

Score a prospect against the Artefact 14.5-point ICP model.

Evaluates Firmographic Fit (5 pts), Behavioral Fit (5 pts), and Strategic Fit (4.5 pts). Returns tier classification (1-4), score breakdown, and recommended engagement strategy.

Provide EITHER company_id (HubSpot ID, requires HUBSPOT_API_KEY) OR company_data (JSON string).

Args: company_id: HubSpot company ID to fetch and score. company_data: JSON string with company attributes. Example keys: industry, annual_revenue, employee_count, geography, tech_stack (list), growth_signals (list), content_engagement ("active"|"occasional"|"none"), purchase_history ("regular"|"occasional"|"never"), decision_maker_access ("c_suite"|"director"|"manager"|"indirect"|"none"), budget_authority ("dedicated"|"shared"|"possible"|"none"), strategic_alignment ("strong"|"partial"|"misaligned"). scoring_config: Optional JSON string to override default scoring parameters. Customize the model for your business. Example keys: primary_industries (list), adjacent_industries (list), excluded_industries (list), revenue_range ([min, max]), employee_range ([min, max]), primary_geography (list), secondary_geography (list).

Returns: JSON with total score, tier, breakdown, exclusion check, and recommended action.

score_pipeline_healthA

Analyze pipeline health with velocity metrics, conversion rates, and at-risk detection.

Calculates overall health score (0-100), identifies bottleneck stages, measures stage-to-stage conversion rates, and flags stalled or overdue deals.

Args: pipeline_id: Optional HubSpot pipeline ID to filter. Default: all pipelines. source: "auto" (uses HubSpot if API key is set, otherwise sample data), "hubspot" for live data, "sample" for built-in demo data.

Returns: JSON with health score, velocity metrics, conversion rates, at-risk deals, and stage distribution.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
scoring_modelICP 14.5-point scoring model reference.
tier_definitions4-tier classification system (Ideal / Strong / Moderate / Poor).
rfm_segments11 RFM segment definitions with scoring scales.
spiced_frameworkSPICED discovery framework reference.
server_versionServer version and status information.

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