Paywatch

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

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ paywatch-emit --version
paywatch 1.0.0

$ paywatch-emit --help
usage: paywatch [-h] [--version] {scan} ...

Detect recurring charges and subscriptions from a bank/Plaid CSV.

positional arguments:
  {scan}
    scan      Scan a CSV for recurring charges.

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

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

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

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Network Traffic",
        "description": "Potential malicious activity detected on port 443.",
        "created_at": "2023-02-20T14:30:00Z",
        "updated_at": "2023-02-20T14:30:01Z",
        "labels": ["Network", "Malware"],
        "observables": [
            {
                "type": "IP",
                "value": "192.168.1.100"
            },
            {
                "type": "Domain",
                "value": "example.com"
            }
        ]
    }
]
}

Usage — step by step

paywatch detects recurring charges and subscriptions from a bank/Plaid transactions CSV.

1. Install:

   pip install -e .
   paywatch --version
   

2. Scan a transactions CSV for recurring charges:

   paywatch scan transactions.csv
   

3. Focus on waste — show only subscriptions that look forgotten/unused:

   paywatch scan transactions.csv --forgotten-only
   

4. Read the output as JSON (summary + per-subscription cadence, next charge, annualized cost):

   paywatch scan transactions.csv --format json | jq '.summary'
   

5. Automate — pipe a monthly export through paywatch and archive the JSON report:

   paywatch scan "$HOME/exports/$(date +%Y-%m).csv" --format json > subs.json
   

Contents

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

Why paywatch?

consumer+SMB crossover, viral

paywatch 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

• ✅ Normalize Merchant
• ✅ Load Transactions
• ✅ Detect Subscriptions
• ✅ Summarize
• ✅ Subscription To Dict
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

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

Example

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

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[input] --> P[paywatch<br/>analyze + score]
  P --> OUT[report]

Use it from any AI stack

paywatch is interoperable with every popular way of using AI:

• MCP server — paywatch mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe paywatch 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 paywatch	Rocket Money
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 Rocket Money, 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 (paywatch 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/paywatch.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/paywatch.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/paywatch.git" # uv
pip install cognis-paywatch                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/paywatch:latest --help        # Docker
brew install cognis-digital/tap/paywatch                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/paywatch/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/paywatch	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• invoctl — CLI invoicing + payment-link generator with PDF and a local ledger
• churnlens — Self-hosted SaaS metrics — MRR, churn, LTV from Stripe or CSV
• 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

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 paywatch 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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