Introduction

MaiMap is a service which analyzes your entire distributed codebase and provides that information to you via a web interface and empowers your LLM via an MCP server.

How is it different from existing AI solutions?

Most existing LLM-based code editors use a naive approach of providing their AI with text-based search capabilities for an entire codebase. MaiMap uses a combination of rule-based and LLM-based static code analysis to parse your codebase(s) into a deep contextual map. That map is stored in a graph database and served to your LLM model via an MCP server.

This allows a MaiMap-enabled LLM to answer prompts that they would otherwise be incapable of answering. For example:

• “Describe the overall architecture of my microservices”
• “What are the bounded contexts of my services?”
• “Which endpoints in the auth-service query the user_permissions table in Postgres?”
• “Trace the series of events, API calls and side-effects that happen when a user signs up”