Hundreds of endpoints distilled into two intelligence tools. 🛠️
At WRITER, we’re building an MCP gateway to empower our customers to connect hundreds of services and thousands of tools in a maximally secure, transparent manner.
The problem? When it comes to security and scalability – MCP leaves a lot to the end user to figure out.
Our own Dennis Thompson 🍉 broke down some of the key insights our engineering team is uncovering while building out our MCP implementation. He shares some of the initial challenges we faced – like context rot and tool calling accuracy – and how we distilled hundreds of API endpoints down to just two intelligent tools.
Check it out: https://t.co/Eh3Qa6fYZI
MCP — The Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.
distillation — Training a small, cheap model to imitate a big one's outputs, keeping much of the capability at a fraction of the cost.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
Why it matters
Tool-count explosion is the practical ceiling on large MCPThe Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.Full definition → deployments. Collapsing hundreds of endpoints into two dispatch tools is a concrete pattern for keeping context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → small and tool selection accurate.
