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1 month ago
glama

MCP TokenSage

Enables token counting, usage tracking, and cost calculation for LLM APIs, with a proxy server mode to automatically intercept and monitor API requests from clients like Cursor and Windsurf.

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// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 1 credential: GITHUB_CLIENT_SECRET
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// required environment variables
This server reads these from process.env. You'll be asked to provide them before it can run.
configCODEX_HOMECodex CLI ~/.codex/ %USERPROFILE%\.codex\ Configurable via env var ([source](https://github.com/openai/codex))
configCSRF_ALLOWED_ORIGINS
configDATABASE_URL
configGITHUB_CLIENT_ID
🔐 secretGITHUB_CLIENT_SECRET
configNEXT_PUBLIC_URL
configSUBMISSION_FRESHNESS_DAYS
configTOKSCALE_LIBC
configXDG_DATA_HOMEimg width="48px" src=".github/assets/client-crush.png" alt="Crush" /> [Crush](https://crush.ai/) $/crush/projects.json (project registry; fallback: ~/.local/share/crush/projects.json) ✅ Yes
// full audit trail
The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.
// improvement guidance — verified publishers only
We have 1 concrete improvement we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/quangminh1212-xlab-token-3752ti)](https://m8ven.ai/mcp/quangminh1212-xlab-token-3752ti)
commit: bd03c6d4cc72c657dadf2606ccc607facfea7834
code hash: f7d73f35ba1011cebfcf7814d48620a47936295841439d1a07db11ee85a8b790
verified: 6/29/2026, 11:15:35 AM
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