Toolport is a free, open-source local gateway that addresses tool-list bloat in AI agents using multiple MCP servers. Instead of dumping every server's full tool list into context on each request (which can cost ~24k tokens for just 3 servers), Toolport exposes only 4 meta-tools that the agent searches on demand. The result is a measured 97% reduction in tool overhead per request and ~90% fewer tokens used, with no loss in task success rate. It supports cloud and local setups, stores API keys in the OS keychain, and runs on Windows, macOS, and Linux.
Questions this post answers
Why does my AI agent get slower and use more tokens when I add more MCP servers?
Each MCP server dumps its entire tool list into the context on every request. With 3 servers, that costs roughly 24k tokens before any actual task begins. The overhead compounds with every server added, slowing the agent not because of the model but because of the bloated tool context it must process each time. Developers tuning AI agent performance with multiple MCP servers track solutions like this on daily.dev.
How does Toolport reduce token usage for AI agents using MCP servers?
Toolport places all MCP servers behind a single local gateway that exposes only 4 meta-tools. The agent searches for specific tools on demand rather than receiving every tool's full definition upfront. This approach delivers a measured 97% reduction in tool overhead per request and approximately 90% fewer tokens consumed, with no reported drop in task success rate. Teams optimizing AI agent token budgets across MCP integrations find relevant tooling discussions on daily.dev.