Quickstart

Get from zero to semantic search in 5 minutes.

Prerequisites

• Node.js 22+ installed
• Cursor IDE (or Claude Code)
• A code repository to index

Step 1: Install dev-agent

npm install -g @lytics/dev-agent

Step 2: Index your repository

cd ~/your-project
dev index .

You’ll see output like:

Scanning repository...
Found 247 files to index
Generating embeddings...
████████████████████████████████████████ 100%
Indexed 1,832 code components in 12.3s

Step 3: Connect to Cursor

dev mcp install --cursor

Then restart Cursor.

Step 4: Try semantic search

Open Cursor’s AI chat and ask:

“Use dev_search to find where we handle user authentication”

You’ll get results like:

1. [89%] class: AuthMiddleware (src/auth/middleware.ts:15)
2. [84%] function: verifyToken (src/auth/jwt.ts:5)
3. [72%] function: validateSession (src/auth/session.ts:23)

Step 5: Explore more tools

Try these prompts:

Planning from GitHub issues:

“Use dev_plan to create an implementation plan for issue #42”

Find similar code:

“Use dev_explore to find code similar to src/utils/cache.ts”

Search GitHub issues:

“Use dev_gh to search for issues about performance”

What’s Happening Under the Hood

When you run dev index .:

1. Scanner parses your code using the TypeScript Compiler API
2. Extractor identifies functions, classes, interfaces, types, arrow functions, hooks, and exported constants
3. Embedder generates vector embeddings locally (MiniLM-L6-v2)
4. Storage saves everything to LanceDB (~/.dev-agent/indexes/)

When AI tools call dev_search:

1. Query gets embedded using the same model
2. Vector search finds semantically similar code
3. Formatter returns results optimized for LLM context windows

Next Steps

• MCP Tools → — Learn about all available tools
• Architecture → — Understand how dev-agent works

Pro tip: Re-index after major code changes to keep search results accurate:

dev index . --force