gasp-standard-mcp

MCP server for the GASP Standard — the Generally Accepted SaaS Principles standard for metric definitions, formulas, benchmarks, and relationships.

Works with Claude Code, Claude Desktop, or any MCP-compatible client.

Install

Claude Code (one command)

claude mcp add gasp-standard -- npx -y gasp-standard-mcp

Manual config

Add to your project .mcp.json or ~/.claude/settings.json:

{
  "mcpServers": {
    "gasp-standard": {
      "command": "npx",
      "args": ["-y", "gasp-standard-mcp"]
    }
  }
}

Restart your MCP client after adding the config.

Tools

| Tool | Description | |------|-------------| | lookup_metric | Full metric details: definition, formula, benchmarks, entity, common mistakes, sources | | list_metrics | List all metrics, optionally filtered by department and/or signal type | | get_formula | Get formula(s) for a metric | | get_relationships | Upstream/downstream relationships for metrics, entities, or concepts — 21 relationship types across signal, lifecycle, ownership, interaction, and financial flow categories | | get_data_requirements | Data requirements for implementing a metric: fields, types, grain, source, and example SQL | | search | Full-text search across metrics, definitions, and data requirements | | generate_query | Generate warehouse-specific SQL from a metric name + adapter mapping | | validate_adapter | Validate a GASP adapter mapping file — reports which metrics are fully/partially/not covered | | infer_drivers | Diagnose what could explain an observed metric movement — ranked upstream candidates with paths and per-step edge classifications | | explain_path | Enumerate edge chains between two metrics, with classification (metric_signal / structural / lifecycle / behavioral / assignment / generative) per step | | coverage_gap | Audit a metric set: identify one-hop upstream/downstream metrics not in the set, plus any disconnected metrics |

The traversal tools (infer_drivers, explain_path, coverage_gap) return structure — paths, classifications, attenuation scores — not numeric forecasts. They serve diagnosis, exploration, and coverage-audit workflows respectively, and compose: use infer_drivers to pick candidates, explain_path to scrutinise a chain, then coverage_gap to check whether the candidate is being measured. For counterfactual "what if" simulation, use the TWIN Modifier.

Data

• 300 metrics across 13 departments
• 92 glossary definitions (80 SaaS domain + 12 GASP framework)
• 82 relationship nodes (60 metrics + 15 entities + 7 concepts), 164 edges
• 21 relationship types: metric signal (drives, reduces, predicts, component, measures), entity lifecycle (converts_to, parent_of, belongs_to), entity ownership (owns, grants, priced_by), entity interactions (manages, serves, engages_via, submits, represented_by, sources), entity financial flows (generates, produces, contributes_to, incurs)
• 78 data requirements with field types, grain, and example SQL
• 15 business entities (Customer, Subscription, License, Lead, Opportunity, User, Ticket, Employee, Invoice, Partner, Project, Plan, Product, Campaign, Contact)
• 7 business concepts (Revenue, Bookings, COGS, Cohort, Pipeline, Segment, TCV)
• 22 source categories, 198 canonical fields
• 60 structured formulas with decomposed inputs (metric refs + field refs)
• 60 temporal mappings (grain, frequency, period for every metric node)
• Access control classifications for every graph metric (sensitivity tier + access scope)
• CEL change_nature field for revenue quality analysis (Adjusted NRR/GRR)
• Per-department cross-references (e.g. NRR under Customer Success, Gross Margin under Finance) now resolve to the full canonical content via slug lookup
• Sources: the canonical GASP Standard files

Examples

Once installed, ask your AI assistant:

Definitions and structure

• "What is NRR?"
• "How do I calculate CAC Payback?"
• "What drives ARR?"
• "How does Customer relate to Subscription?"
• "What sensitivity tier is CAC classified as?"
• "What does confidential mean in GASP?"
• "How does Plan relate to Subscription?"
• "Which campaigns source leads into the pipeline?"
• "List all marketing metrics"
• "What data do I need to implement ARR tracking?"
• "Search for churn"

Diagnosis, exploration and coverage (new in 1.9.0)

• "ARR is down this month. What could explain it?" — infer_drivers
• "How does Win Rate eventually affect Free Cash Flow?" — explain_path
• "We track ARR, NRR, GRR, CAC and CAC Payback. What important metrics are we missing?" — coverage_gap
• "Why might NRR be slipping? Trace the path back through Health Score." — composes infer_drivers → explain_path

License

Apache-2.0