# Install dependencies
npm install

# Build the project
npm run build

# Create DXT package
npm run build:dxt

# Pack the final .dxt file for distribution
dxt pack

# View logs (macOS)
open "$HOME/Library/Logs/Claude/mcp-server-PDF Agent MCP.log"

# Stream logs in real-time (macOS)
tail -f "$HOME/Library/Logs/Claude/mcp-server-PDF Agent MCP.log"

# Clear/delete logs (macOS)
rm "$HOME/Library/Logs/Claude/mcp-server-PDF Agent MCP.log"

# View logs (Windows)
notepad "%LOCALAPPDATA%\Claude\Logs\mcp-server-PDF Agent MCP.log"

# Clear/delete logs (Windows)
del "%LOCALAPPDATA%\Claude\Logs\mcp-server-PDF Agent MCP.log"

When working with PDFs using the PDF Agent MCP tools, follow this strategic approach:

### 1. Query Analysis & PDF Identification
- **Think carefully** about the user's search query and information needs
- **Identify which PDF(s)** are most likely to contain the answer
- Consider the document type, domain, and likely structure based on the query

### 2. Exploratory Phase (Always Start Here)
- **Get metadata** first using `get_pdf_metadata` to understand document size, creation date, and properties
- **Extract table of contents** with `get_pdf_outline` to understand document structure and navigation
- **Analyze the outline** to identify which sections are most relevant to the query

### 3. Strategic Content Extraction
Based on the outline and metadata:
- **Use page ranges** (`"5:10"`, `"20:"`) to focus on specific sections rather than entire documents
- **Extract images** with `get_pdf_images` when visual content is critical (charts, diagrams, tables, equations)
- **Choose text extraction strategy**: `hybrid` (default) for most cases, `native` for clean PDFs, `ocr` for scanned documents

### 4. Advanced Search Strategies
- **Use multiple search queries** with different keywords and synonyms
- **Apply regex patterns** for flexible matching: `/budget|cost|expense/gi` instead of single terms
- **Combine searches**: Start broad, then narrow down with specific terms
- **Use context characters** (150+ chars) to understand search result context
- **Implement early stopping** with `max_results` for large documents

### 5. Iterative Refinement
- **Start with targeted searches** based on outline analysis
- **Follow up with broader searches** if initial queries don't yield results
- **Extract specific page ranges** identified through search results
- **Use visual analysis** (images) when text extraction seems incomplete or when layout matters

### 6. Performance Optimization
- **Avoid processing entire large PDFs** - always use page ranges when possible
- **Use search with early stopping** before extracting large sections
- **Prefer search over full text extraction** for finding specific information
- **Extract images selectively** only when visual analysis is needed

### 7. Multi-Document Workflows
- **Process documents in parallel** when comparing multiple PDFs
- **Use consistent search terms** across documents for comparison
- **Combine results strategically** rather than processing everything at once

### Key Principles:
- **Strategic before comprehensive**: Understand document structure before diving deep
- **Search before extract**: Use pattern matching to locate relevant content first  
- **Visual when necessary**: Extract images only when text extraction is insufficient
- **Iterative refinement**: Start targeted, expand scope as needed
- **Context preservation**: Always maintain enough context around search results

This approach maximizes efficiency, minimizes token usage, and provides more accurate, focused results than traditional "dump entire PDF" methods.

{
  "mcpServers": {
    "pdf-agent": {
      "command": "node",
      "args": [
        "PATH_TO_REPO/server/index.js"
      ]
    }
  }
}