Introducing Gabb: Local Code Intelligence for AI Assistants
AI coding assistants have transformed how developers work. Tools like Claude Code, Cursor, and GitHub Copilot can generate code, explain complex logic, and help debug issues faster than ever before. But there’s a fundamental problem: they don’t actually understand your codebase.
Today, we’re introducing Gabb—a local code indexing CLI that gives AI assistants the context they need to work effectively with your code.
The Context Problem
When you ask an AI assistant to “find where user authentication is handled” or “show me all implementations of the PaymentProcessor interface,” it has to search. And search. And search some more.
Without prior knowledge of your codebase structure, AI assistants resort to:
- Broad file glob patterns hoping to find relevant files
- Grep searches across thousands of files for keyword matches
- Reading entire files when they only need a single function
- Repeated searches because they forgot what they found earlier
This isn’t the AI’s fault—it’s working with what it has. But the result is slow, token-expensive, and often inaccurate assistance.
We’ve measured this. On typical development tasks, an AI assistant without codebase context spends 60-70% of its time just finding the right files. That’s time you’re waiting. That’s tokens you’re burning. That’s context window you’re exhausting.
What Gabb Does
Gabb builds and maintains a semantic index of your codebase. It understands:
- Every symbol in your code—functions, classes, interfaces, types, variables
- Where they’re defined down to the exact line and column
- How they relate to each other—implementations, extensions, trait implementations
- Where they’re used across your entire codebase
This index lives locally in a SQLite database. Your code never leaves your machine.
When an AI assistant needs to navigate your code, Gabb provides instant answers:
"Where is the UserService class defined?"
→ src/services/user.ts:45
"What implements the Repository interface?"
→ UserRepository (src/repositories/user.ts:12)
→ ProductRepository (src/repositories/product.ts:8)
→ OrderRepository (src/repositories/order.ts:15)
"Show me the structure of auth.rs"
→ [Functions: login, logout, validate_token, refresh_session]
[Structs: AuthConfig, Session, TokenClaims]
[Impls: Session, TokenClaims]
No searching. No guessing. Sub-millisecond responses.
How It Works
Gabb runs as a daemon that watches your codebase for changes. On first run, it performs a full index of your codebase. After that, it incrementally updates only the files that change. The daemon uses minimal resources—it’s designed to run continuously without you noticing.
The index integrates with AI assistants through the Model Context Protocol (MCP). For Claude Code users, setup is simple:
brew install gabb-software/tap/gabb
gabb setup
claude mcp add gabb -- gabb mcp-server
# Then restart Claude Code
For other platforms, see installation instructions.
This registers Gabb’s tools with Claude Code. From then on, your AI assistant can:
- Jump to definitions instantly instead of searching
- Find implementations of interfaces and abstract classes
- Discover usages of any symbol across your codebase
- Preview file structure before reading (saving tokens)
Language Support
Gabb currently supports semantic indexing for:
| Language | Extensions |
|---|---|
| TypeScript | .ts, .tsx |
| Python | .py, .pyi |
| Rust | .rs |
| Kotlin | .kt, .kts |
| C++ | .cpp, .cc, .cxx, .hpp, .hh |
Each language has a dedicated parser built on tree-sitter, ensuring accurate symbol extraction regardless of code complexity.
Privacy by Design
Your code is yours. Gabb:
- Runs entirely locally—no cloud services, no API calls, no telemetry
- Stores indexes on your machine—in a SQLite database you control
- Works offline—internet connection not required
- Respects .gitignore—automatically excludes files you don’t want indexed
This isn’t just a feature—it’s a core design principle. Code intelligence should enhance your workflow without compromising your code’s privacy.
The Results
We’ve been testing Gabb extensively with Claude Code on real-world development tasks. The improvements are significant:
- 40-60% reduction in task completion time for navigation-heavy work
- Fewer tool calls as the AI finds the right files on the first try
- Lower token usage from targeted file reads instead of full file scans
- More accurate responses because the AI understands code relationships
These aren’t synthetic benchmarks—they’re measurements from actual development workflows: bug fixes, feature implementations, refactoring tasks.
Getting Started
Gabb is open source and available today. For Claude Code users on macOS:
brew install gabb-software/tap/gabb
gabb setup
claude mcp add gabb -- gabb mcp-server
# Then restart Claude Code
For other platforms, see installation instructions.
That’s it. Your AI assistant now has semantic understanding of your codebase.
What’s Next
This is just the beginning. We’re actively working on:
- More language support—Go, Java, and C are on the roadmap
- Enhanced cross-file analysis—better tracking of type flows and call hierarchies
- Performance optimizations—faster indexing for very large codebases (5M+ LOC)
We’re building Gabb in the open and welcome contributions. Check out our GitHub repository to see the code, report issues, or submit pull requests.
Try It Today
If you use AI coding assistants, give Gabb a try. The difference between an AI that searches your code and one that understands your code is substantial—and once you experience it, you won’t want to go back.
Your code deserves an AI that knows where everything is.
Gabb is open source software released under the MIT license. We’d love to hear your feedback—find us on GitHub.