TOKENMETER

Token and cost counter / budgeter for LLM apps, CI-ready

Developer Tools — fast, single-purpose, CI- and agent-friendly.

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

Usage — step by step

1. Install (Python 3.9+):

   pip install tokenmeter

2. Count tokens and estimate cost for some text or a file, against a pricing model:

   tokenmeter count -f prompt.txt -m claude-sonnet --output-tokens 500
   tokenmeter count -t "hello world" -m claude-sonnet

3. List known models and their pricing:

   tokenmeter models --format json | jq .

4. Batch-estimate many files and roll them up:

   tokenmeter batch prompts/*.txt -m claude-sonnet

5. Gate a budget in CI. budget exits 1 when the cost/token cap is exceeded:

   tokenmeter budget -f prompt.txt -m claude-sonnet --max-cost 0.05 || echo "Over budget"

Contents

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

Why tokenmeter?

AI cost control

tokenmeter 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.

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Features

• ✅ Add Model
• ✅ Get Pricing
• ✅ List Models
• ✅ Count Tokens
• ✅ Estimate
• ✅ Check Budget
• ✅ Aggregate
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

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

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Example

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

  2 findings · risk score 5 · 38ms

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Architecture

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

Loading

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Use it from any AI stack

tokenmeter is interoperable with every popular way of using AI:

• MCP server — tokenmeter mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe tokenmeter 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

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How it compares

	Cognis tokenmeter	tiktoken
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 tiktoken, re-framed the Cognis way. Missing a credit? Open a PR.

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Integrations

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

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Install — every way, every platform

pip install "git+https://github.com/cognis-digital/tokenmeter.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/tokenmeter.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/tokenmeter.git" # uv
pip install cognis-tokenmeter                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/tokenmeter:latest --help        # Docker
brew install cognis-digital/tap/tokenmeter                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/tokenmeter/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/tokenmeter	DEPLOY.md (AWS/Azure/GCP/k8s)

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Related Cognis tools

• mcpforge — Scaffold, test, and publish MCP servers in minutes
• promptlint — Lint, version, and test prompts as code with a CI gate
• envdoctor — .env validator, secret-presence and config-drift checker
• apidiff — Breaking-change detector for OpenAPI / GraphQL across commits
• codeglance — Repo onboarding map — architecture + hotspots for humans and agents
• flakefinder — Flaky-test detector from CI history with quarantine suggestions

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

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Contributing

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

⭐ If tokenmeter 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 (licensing@cognis.digital). See LICENSE.

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_{Cognis Digital · one of 170+ tools in the Cognis Neural Suite · Making Tomorrow Better Today}