pip install cognis-churnlens
churnlens scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ churnlens-emit --version
churnlens 0.1.0

$ churnlens-emit --help
usage: churnlens [-h] [--version] {report,mrr} ...

Self-hosted SaaS metrics: MRR, churn, LTV from a CSV ledger.

positional arguments:
  {report,mrr}
    report      full per-month metrics report
    mrr         latest-month MRR movement summary

options:
  -h, --help    show this help message and exit
  --version     show program's version number and exit

Blocks above are real churnlens output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"findings": [
    {
        "id": "123456",
        "title": "Suspicious Network Traffic",
        "description": "Potential malicious activity detected on network 192.168.1.100",
        "created": "2023-02-20T14:30:00Z",
        "updated": "2023-02-20T14:30:01Z",
        "labels": ["network", "malware"],
        "observables": [
            {
                "type": "ip-dst",
                "value": "192.168.1.100"
            },
            {
                "type": "domain-name",
                "value": "example.com"
            }
        ]
    }
]
}

Usage — step by step

1. Install:

   pip install -e .
   

2. Run a full metrics report from a subscription-event CSV ledger with the report subcommand:

   churnlens report ledger.csv
   

   The report prints current MRR, ARR run-rate, active customers, average customer churn, and a per-month table (MRR end, net-new MRR, customer churn, net revenue churn, LTV).

3. Get the latest-month MRR movement with the mrr subcommand — a breakdown of new / expansion / reactivation / contraction / churned MRR:

   churnlens mrr ledger.csv
   

4. Read / use the output. Both subcommands accept --format json for piping into dashboards and --currency to label amounts (default USD):

   churnlens report ledger.csv --format json --currency EUR
   

5. Use it in automation — recompute metrics on every ledger update and publish the JSON:

   churnlens report ledger.csv --format json > metrics.json
   # feed metrics.json to your BI/dashboard pipeline
   

Contents

• Why churnlens? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why churnlens?

own your SaaS metrics, no per-seat fee

churnlens is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

Features

• ✅ Parse Events
• ✅ Load Events
• ✅ Compute Report
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

pip install cognis-churnlens
churnlens --version
churnlens scan .                       # scan current project
churnlens scan . --format json         # machine-readable
churnlens scan . --fail-on high        # CI gate (non-zero exit)

Example

$ churnlens scan .
  [HIGH    ] CHU-001  example finding             (./src/app.py)
  [MEDIUM  ] CHU-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[capture / scan] --> P[churnlens<br/>parse + map]
  P --> OUT[report]

Use it from any AI stack

churnlens is interoperable with every popular way of using AI:

• MCP server — churnlens mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe churnlens scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

How it compares

	Cognis churnlens	Baremetrics
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Built in the spirit of Baremetrics, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (churnlens mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/churnlens.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/churnlens.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/churnlens.git" # uv
pip install cognis-churnlens                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/churnlens:latest --help        # Docker
brew install cognis-digital/tap/churnlens                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/churnlens/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/churnlens	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• invoctl — CLI invoicing + payment-link generator with PDF and a local ledger
• leadforge — Lightweight MCP-native CRM pipeline with email sequences
• quotecraft — Proposal / quote / SOW generator — YAML to branded PDF
• boardroom — Investor-update and KPI one-pager generator from your metrics
• seataudit — SaaS license, seat-usage and shadow-IT auditor
• paywatch — Recurring-charge and subscription detector from bank/Plaid CSV

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If churnlens saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license ([email protected]). See LICENSE.

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