How I turned fragmented LLM quotas into one larger token budget with an MCP server

If you use coding agents heavily, you have probably run into the same annoying pattern I did. One provider is rate-limited. Another still has quota left. A third is cheaper for simple tasks but not what your current workflow is wired to use. In practice, that means your session stops anyway, even though you still have perfectly usable model capacity somewhere else. I built @mrrlin-dev/external-agents to fix that problem. It is an MCP server that lets tools like Codex and Claude Code route work across multiple LLM providers through one interface. The main value is not "AI magic." It is much more boring and useful than that: better cost efficiency a larger effective token budget fewer rate-limit interruptions less custom fallback logic glued into every workflow The actual problem Most agent setups still assume one provider at a time. That is fine until you start doing real work: long review sessions multi-file edits repeated reviewer passes large-context analysis par