Announcing Flyto Indexer: Enhanced AI Code Refactoring with Source Dependency Analysis

Flyto Indexer is an open-sourced MCP server designed to assist AI with comprehensive code base analysis for more effective refactoring. Unlike standard AI tools that often lack a deeper understanding of code dependencies, Flyto Indexer uses an AST-based system to construct a real symbol graph of your repository. This forensic view aids AI tools, like Claude, in understanding who calls a function, what files depend on it, its scope across projects, and which parts of the code are dead and could potentially be deleted.

Key Details

The server provides 23 specific tools including impact_analysis, find_references, dependency_graph, cross_project_impact, and find_dead_code. For example, when you instruct Claude to rename a function, such as validateOrder to validate_order, Flyto Indexer identifies:

• 5 call sites
• 3 affected files
• impacted areas including frontend and tests
• a medium-level risk associated with the change

Once the analysis is complete, it updates the entire codebase accordingly, reducing the guesswork involved in such operations. The tool relies purely on Python and its standard library, avoiding the use of embeddings, vector databases, or external services.

Setting up Flyto Indexer is straightforward, requiring just a couple of commands:

pip install flyto-indexer
flyto-index scan .
flyto-index serve

It integrates seamlessly with tools like Claude Code, Cursor, and Windsurf, or any MCP client, under an MIT license. Questions for users to consider include whether cross-project impact analysis is required and if the tool should be integrated as part of CI before merging AI-generated changes. The tool's developers are also keen to learn which programming languages should be prioritized for future updates.