pip install cognis-churnlens
churnlens scan . # → prioritized findings in seconds-
Install:
pip install -e . -
Run a full metrics report from a subscription-event CSV ledger with the
reportsubcommand: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).
-
Get the latest-month MRR movement with the
mrrsubcommand — a breakdown of new / expansion / reactivation / contraction / churned MRR:churnlens mrr ledger.csv
-
Read / use the output. Both subcommands accept
--format jsonfor piping into dashboards and--currencyto label amounts (defaultUSD):churnlens report ledger.csv --format json --currency EUR
-
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
- Why churnlens? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing
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.
- ✅ Parse Events
- ✅ Load Events
- ✅ Compute Report
- ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
- ✅ Ports in Python, JavaScript, Go, and Rust (
ports/)
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)$ churnlens scan .
[HIGH ] CHU-001 example finding (./src/app.py)
[MEDIUM ] CHU-002 another signal (./config.yaml)
2 findings · risk score 5 · 38ms
flowchart LR
IN[capture / scan] --> P[churnlens<br/>parse + map]
P --> OUT[report]
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 jsoninto 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
| 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.
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.
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) |
invoctl— CLI invoicing + payment-link generator with PDF and a local ledgerleadforge— Lightweight MCP-native CRM pipeline with email sequencesquotecraft— Proposal / quote / SOW generator — YAML to branded PDFboardroom— Investor-update and KPI one-pager generator from your metricsseataudit— SaaS license, seat-usage and shadow-IT auditorpaywatch— Recurring-charge and subscription detector from bank/Plaid CSV
Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram
PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.
{} 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.
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 (licensing@cognis.digital). See LICENSE.