Graphify C# brings compiler-accurate 'Find Usages' to AI coding agents
The open-source tool replaces unreliable grep-based retrieval with a knowledge graph to reduce hallucinations and token costs.
Developer zachsaw has released Graphify C#, an open-source tool that provides AI coding agents with compiler-accurate 'Find Usages' capabilities for C#. The tool, which supports C# 15 syntax via the .NET 11 asset, is available via NuGet as 'Graphify.CSharp'.
Graphify C# is part of a broader ecosystem backed by Y Combinator that transforms codebases into queryable knowledge graphs. Unlike traditional retrieval methods that rely on simple text searches (grep) or vector embeddings, Graphify uses a knowledge graph approach. This allows AI assistants to trace precise paths through a codebase and cite evidence for their changes. The system integrates with 17 AI assistants, including Cursor, Copilot, Aider, and Claude Code, frequently utilizing an MCP server for connectivity. The project follows an open-core model under the Apache 2.0 license.
The shift from RAG to graphs
Most current AI coding assistants rely on Retrieval-Augmented Generation (RAG) using vector embeddings. While useful for general queries, this often results in "blind searches" where the AI misses critical dependencies or hallucinates connections that do not exist. By building a typed code graph using tree-sitter grammars, Graphify enables deterministic AST extraction and multi-hop reasoning across entire repositories. This ensures that when an agent searches for where a method is used, it receives a compiler-accurate list rather than a list of similar-looking text strings.
Impact on reliability and cost
Providing agents with accurate dependency mapping allows them to understand the "blast radius" of a code change before it is merged, significantly increasing the reliability of AI-generated PRs. Beyond accuracy, the precision of graph-based retrieval drastically lowers the amount of irrelevant context sent to the LLM. This efficiency leads to substantial cost savings; for instance, Steve Scargall of MemVerge reported a token reduction of up to 79x when using the system.
Future outlook
As AI agents move from simple autocomplete to autonomous feature implementation, the need for deterministic codebase navigation becomes critical. The release of Graphify C# extends these capabilities to the .NET ecosystem, bridging the gap between the deep static analysis found in professional IDEs and the flexible reasoning of LLMs. Developers can now integrate these capabilities into their existing AI workflows via the NuGet package and MCP server.