ChurnLens

io.github.kindrat86v1.0.1更新於 Oct 6, 2026

Buyer-side SaaS due-diligence maths: NRR, GRR, revenue concentration, zombie MRR, LTV:CAC.

已驗證Streamable HTTP可網頁執行FinanceData & Analytics

概覽

AI 產生的概覽

根據你提供的彙總數據，計算買方觀點的 SaaS 盡職調查指標，例如 NRR、GRR、營收集中度、殭屍 MRR 與 LTV:CAC。

功能
ChurnLens 提供六個用於 SaaS 盡職調查的計算工具：calculate_churn_rate（NRR、GRR、營收流失、年化流失率以及 NRR-GRR 差距）、analyze_revenue_concentration（赫芬達爾-赫希曼指數與前 N 大客戶營收占比）、detect_zombie_mrr（仍在付費但已休眠的帳戶及其面臨風險的 ARR）、score_saas_health（0-100 綜合評分與最弱面向）、calculate_ltv（毛利調整後的 LTV、LTV:CAC 與 CAC 回收期）以及 get_scoring_bands（各工具採用的門檻值）。工具除了文字區塊外也回傳 structuredContent，讓代理直接取得結構化數字。所有結果都根據呼叫方提供的彙總數據計算。
適用情境
適合收購方、私募股權機構與併購分析師對 SaaS 標的做初步篩選，也適合希望以一致口径計算留存與效率指標的人。它只是篩選輔助工具，不能取代客戶層級分析，例如世代衰減曲線或續約懸崖時點。
執行需求
遠端 streamable HTTP 端點 churnlens.site/api/mcp；未宣告需要帳號、身分驗證、API 金鑰或環境變數。使用 stdio 的用戶端可透過 npx mcp-remote 橋接存取，這需要 Node.js。
安裝前請注意
該伺服器聲明不儲存傳送給它的內容，但你提供的數據仍會傳輸到第三方端點。評分區間是參考公開基準得出的門檻值，並非實測調查資料，不應當作調查結果呈現。結果品質取決於所提供的彙總數據，無法反映客戶層級效應。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 ChurnLens，將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable，透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "churnlens": {
      "type": "http",
      "url": "https://churnlens.site/api/mcp"
    }
  }
}

README

ChurnLens MCP server

Buyer-side SaaS due-diligence maths for AI agents. Net and gross revenue retention, revenue concentration risk, dormant ("zombie") MRR, LTV:CAC and a composite health score — computed from figures you supply.

Live endpoint: https://churnlens.site/api/mcp — streamable HTTP, MCP protocol 2024-11-05. No authentication, no account, no rate limit, and nothing you send is stored.

Install

Claude Desktop, Claude Code, or any client that speaks stdio:

bash
npx mcp-remote https://churnlens.site/api/mcp

By config:

json
{  "mcpServers": {    "churnlens": {      "command": "npx",      "args": ["mcp-remote", "https://churnlens.site/api/mcp"]    }  }}

A GET on the endpoint returns the manifest. The machine-readable descriptor is at /.well-known/mcp.json.

Tools

ToolWhat it returns
calculate_churn_rateNRR, GRR, revenue churn, correctly compounded annualised churn, and the NRR−GRR spread that exposes churn masked by expansion
analyze_revenue_concentrationHerfindahl-Hirschman Index, top-N revenue share, and which customers are large enough that losing one is a balance-sheet event
detect_zombie_mrrAccounts still paying but dormant past a threshold, and the ARR at risk behind them
score_saas_healthComposite 0–100 across retention, growth, concentration, efficiency and durability, plus the weakest dimension
calculate_ltvGross-margin-adjusted lifetime value, LTV:CAC and CAC payback in months
get_scoring_bandsEvery threshold the tools apply, with its provenance

Every tool returns structuredContent alongside the text block, so an agent gets typed numbers rather than prose it has to parse back out.

Example

js
calculate_churn_rate({  starting_mrr:    100000,  expansion_mrr:    37000,  contraction_mrr:   5000,  churned_mrr:      17000})
// nrr_pct: 115, grr_pct: 78, expansion_masking_spread_pts: 37// "A wide NRR-GRR spread: expansion revenue is masking substantial//  churn underneath. Diligence should look at the retained base//  separately from upsell."

A business reporting 115% net revenue retention sounds excellent. The same business at 78% gross revenue retention is losing nearly a quarter of its revenue base a year and covering the hole with upsell. Most dashboards show the first number and not the second.

On the scoring bands

get_scoring_bands returns thresholds, not measured data. They are informed by published industry benchmarks — SaaS Capital, Benchmarkit, Recurly and FE International — cited with sources at churnlens.site/benchmarks. Segment matters enormously: median retention for enterprise infrastructure and for SMB self-serve are not the same number. Do not present a band as though it were a survey result.

What it does not do

These tools compute from summary figures you supply. They cannot see what only emerges from customer-level data — cohort decay curves, renewal-cliff timing, concentration in specific logos. Treat them as a first-pass screen.

Verify the maths yourself

The same calculations are open source under MIT at kindrat86/saas-metrics — zero dependencies, every scoring band documented, 27 tests. A result from this server can be reproduced independently.

Interactive versions for humans, no signup: churnlens.site/free.

About

ChurnLens is a buyer-side SaaS due-diligence tool for acquirers, private-equity firms and M&A analysts.

Unaffiliated with the similarly named churnlens.io (retention automation) or churnlens.tech (churn prediction).

MIT licensed. Free.

來源：README.md，提交 6b80333

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版本歷史

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  1. v1.0.1最新Sep 16, 2026