Infrawise MCP Server Sends AI Agents Only the Schema They Actually Need

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Sending an AI coding assistant your entire database schema on every request wastes thousands of tokens on irrelevant tables and can distract the model from the actual task. Infrawise has built an MCP server designed to solve this by giving agents a lightweight way to discover what infrastructure exists before fetching detailed schema only for the specific tables involved. Three core tools define the approach: a compact overview listing all resources by name, a scoped schema fetcher accepting up to 20 table names at a time, and a full graph dump reserved for cases that genuinely need it. The scoped tool returns columns, keys, indexes, and type information without any row data, and suggests close name matches when a table isn't found. The goal is to reduce context noise, lower token costs, and keep the model focused on the tables a given task actually touches.

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