Answering Structural Questions with BoostGraph

BoostGraph reads your codebase and builds a local map of how it fits together, including what calls what, how files connect, and where key logic lives. This local map enables your agent to answer structural questions without searching file by file.

BoostGraph offers the following benefits:

• Faster answers: One to a few tool calls instead of dozens of discovery steps
• Surgical context: Exact symbols and call paths, not entire directory trees
• Lower cost: Less discovery overhead means fewer tokens per session
• 100% local: No API keys, no data leaves your machine
• 30+ languages: Go, Python, TypeScript, Java, Rust, C#, and more

How Agents Query BoostGraph

BoostGraph runs as an MCP server and exposes a tool that lets a supported coding agent query your codebase with natural-language questions. Manual file searches are not required.

Seamless Indexing

Indexing happens in the background. When you run boost init, JFrog Boost registers hooks on your supported coding agents. At the start of each session, the hook verifies the index:

• First time in a repository: Creates .boost/ and builds the graph quietly while you work.
• Later sessions: Syncs the index to match the current tree.
• After code changes: A local file watcher keeps the index updated.

On large codebases, the first index can take longer, but it runs in the background and does not interfere with your agent. When the index is ready, the agent can use boostgraph_explore to provide you with all the benefits of BoostGraph.

When you open a codebase in a supported agent, indexing starts automatically. You can ask structural questions about flows, architecture, or callers and callees. The agent uses boostgraph_explore instead of long grep-and-read loops. See JFrog Boost Quickstart for setup steps.

Related Topics

• Troubleshooting BoostGraph
• JFrog Boost Quickstart
• Configuring JFrog Boost
• JFrog Boost Overview