As the library of LLMs and their associated tools grow, administrators are pressured to provide auditing, measure adoption, provide tools through MCP, and track token spend. Disparate SAAS platforms provide_some_ of these for_some_ tools, but there is no centralized, secure solution for these challenges.

If you are administrator or devops leader looking to:

- Measure AI tooling adoption across teams or projects

- Provide an LLM audit trail to security administrators

- Manage token spend in a central dashboard


These logs can be used to determine usage patterns, track costs, and evaluate tooling adoption.

This data is currently accessible through the API and CLI (experimental), which we advise administrators export to their observability platform of choice. We've configured a Grafana dashboard to display Claude Code usage internally which can be imported as a starting point for your tooling adoption metrics.

},

{

"title":"AI Bridge",

"description":"Learn about the smart proxy forAI",

"description":"Centralized LLM and MCP proxy forplatform teams",

"path":"./ai-coder/ai-bridge.md",

"icon_path":"./images/icons/api.svg",

"state": ["premium","early access"]