Analytics

pmtoolkit.ai

Provides SaaS business metrics analysis including LTV, CAC, MRR, churn, and unit economics with benchmarks and recommendations.

1 endpoint17 known toolsFirst detected August 8, 2026Last detected August 8, 2026

ENDPOINT 1

https://pmtoolkit.ai/api/mcp

No auth detected

MCP server metadata

Name: pmtoolkit
Version: 1.0.0

Capabilities

tools.listChangedprompts.listChanged

Known tools 17

pm_calculate_ltv

Analyze Customer Lifetime Value with industry-calibrated benchmarks by business segment, health status indicators, and actionable recommendations.

Inferred read-only

pm_calculate_cac

Analyze Customer Acquisition Cost with optional channel breakdown, LTV:CAC ratio assessment, and payback period calculation.

Inferred read-only

pm_calculate_mrr

Analyze MRR/ARR revenue health with SaaS Quick Ratio, Net Revenue Retention (NRR), Gross Revenue Retention (GRR), and composite health scoring.

Inferred read-only

pm_calculate_churn

Analyze customer and revenue churn with business-type-specific benchmarks (B2B SaaS, B2C SaaS, Enterprise, SMB).

Inferred read-only

pm_unit_economics

Get a complete unit economics assessment in one call - LTV, CAC, LTV:CAC ratio, payback period, and churn analysis with an overall health score and strategic recommendations.

Inferred read-only

pm_rice_score

Rank and prioritize a batch of features using the RICE framework (Reach x Impact x Confidence / Effort).

Inferred read-only

pm_ice_score

Rapidly rank and prioritize features using ICE scoring (Impact x Confidence x Ease, all 1-10 scale).

Inferred read-only

pm_classify_impact_effort

Classify features into Impact/Effort Matrix quadrants: Quick Wins (high impact, low effort - do first), Big Bets (high impact, high effort - plan carefully), Fill-ins (low impact, low effort - sprint gaps), and Avoid (low impact, high effort - time sinks).

Inferred read-only

pm_classify_kano

Classify features into Kano Model categories (Must-have, Performance, Delighter, Indifferent, Reverse, Questionable) using functional/dysfunctional survey response pairs.

Inferred read-only

pm_weighted_score

Prioritize features using custom-weighted criteria with statistical analysis.

Inferred read-only

pm_ab_sample_size

Plan A/B tests with statistically rigorous sample size calculations, duration estimates, and feasibility assessment.

Inferred read-only

pm_ab_significance

Determine if your A/B test results are statistically significant with p-value analysis, confidence intervals, Bayesian win probability, and a clear ship/extend/stop recommendation.

Inferred read-only

pm_calculate_roi

Calculate ROI, payback period, and benefit-cost ratio for product investments with optional NPV analysis.

Inferred read-only

pm_market_size

Size your market opportunity with TAM/SAM/SOM analysis using top-down or bottom-up methodology.

Inferred read-only

pm_calculate_conversion

Analyze conversion rates with industry and funnel-stage benchmarks.

Inferred read-only

pm_calculate_nps

Calculate Net Promoter Score with revenue impact modeling, churn risk assessment, word-of-mouth value estimation, and optional segment breakdown.

Inferred read-only

pm_calculate_engagement

Evaluate product engagement with DAU/MAU ratio analysis, engagement tier classification, and industry-calibrated benchmarks.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.pmtoolkit]
url = "https://pmtoolkit.ai/api/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "pmtoolkit": {
      "type": "http",
      "url": "https://pmtoolkit.ai/api/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: pmtoolkit
Remote MCP URL: https://pmtoolkit.ai/api/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "pmtoolkit": {
      "url": "https://pmtoolkit.ai/api/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "pmtoolkit": {
      "type": "http",
      "url": "https://pmtoolkit.ai/api/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "pmtoolkit",
  "transport": "streamable-http",
  "url": "https://pmtoolkit.ai/api/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Trust Data Available

BuiltWith Trust API v2 evidence for pmtoolkit.ai was fetched 2026-08-21T22:54:45.023Z.

Trust status Neutral

pmtoolkit.ai is assessed as Neutral: No suspicious signals found, but no strong positive signal either

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.