skill-seekers-reference/docs/features/PDF_MCP_TOOL.md

# PDF Scraping MCP Tool (Task B1.7)

**Status:** ✅ Completed
**Date:** October 21, 2025
**Task:** B1.7 - Add MCP tool `scrape_pdf`

---

## Overview

Task B1.7 adds the `scrape_pdf` MCP tool to the Skill Seeker MCP server, making PDF documentation scraping available through the Model Context Protocol. This allows Claude Code and other MCP clients to scrape PDF documentation directly.

## Features

### ✅ MCP Tool Integration

- **Tool name:** `scrape_pdf`
- **Description:** Scrape PDF documentation and build Claude skill
- **Supports:** All three usage modes (config, direct, from-json)
- **Integration:** Uses `cli/pdf_scraper.py` backend

### ✅ Three Usage Modes

1. **Config File Mode** - Use PDF config JSON
2. **Direct PDF Mode** - Quick conversion from PDF file
3. **From JSON Mode** - Build from pre-extracted data

---

## Usage

### Mode 1: Config File

```python
# Through MCP
result = await mcp.call_tool("scrape_pdf", {
    "config_path": "configs/manual_pdf.json"
})
```

**Example config** (`configs/manual_pdf.json`):
```json
{
  "name": "mymanual",
  "description": "My Manual documentation",
  "pdf_path": "docs/manual.pdf",
  "extract_options": {
    "chunk_size": 10,
    "min_quality": 6.0,
    "extract_images": true,
    "min_image_size": 150
  },
  "categories": {
    "getting_started": ["introduction", "setup"],
    "api": ["api", "reference"],
    "tutorial": ["tutorial", "example"]
  }
}
```

**Output:**
```
🔍 Extracting from PDF: docs/manual.pdf
📄 Extracting from: docs/manual.pdf
   Pages: 150
   ...
✅ Extraction complete

🏗️  Building skill: mymanual
📋 Categorizing content...
✅ Created 3 categories

📝 Generating reference files...
   Generated: output/mymanual/references/getting_started.md
   Generated: output/mymanual/references/api.md
   Generated: output/mymanual/references/tutorial.md

✅ Skill built successfully: output/mymanual/

📦 Next step: Package with: python3 cli/package_skill.py output/mymanual/
```

### Mode 2: Direct PDF

```python
# Through MCP
result = await mcp.call_tool("scrape_pdf", {
    "pdf_path": "manual.pdf",
    "name": "mymanual",
    "description": "My Manual Docs"
})
```

**Uses default settings:**
- Chunk size: 10
- Min quality: 5.0
- Extract images: true
- Chapter-based categorization

### Mode 3: From Extracted JSON

```python
# Step 1: Extract to JSON (separate tool or CLI)
# python3 cli/pdf_extractor_poc.py manual.pdf -o manual_extracted.json

# Step 2: Build skill from JSON via MCP
result = await mcp.call_tool("scrape_pdf", {
    "from_json": "output/manual_extracted.json"
})
```

**Benefits:**
- Separate extraction and building
- Fast iteration on skill structure
- No re-extraction needed

---

## MCP Tool Definition

### Input Schema

```json
{
  "name": "scrape_pdf",
  "description": "Scrape PDF documentation and build Claude skill. Extracts text, code, and images from PDF files (NEW in B1.7).",
  "inputSchema": {
    "type": "object",
    "properties": {
      "config_path": {
        "type": "string",
        "description": "Path to PDF config JSON file (e.g., configs/manual_pdf.json)"
      },
      "pdf_path": {
        "type": "string",
        "description": "Direct PDF path (alternative to config_path)"
      },
      "name": {
        "type": "string",
        "description": "Skill name (required with pdf_path)"
      },
      "description": {
        "type": "string",
        "description": "Skill description (optional)"
      },
      "from_json": {
        "type": "string",
        "description": "Build from extracted JSON file (e.g., output/manual_extracted.json)"
      }
    },
    "required": []
  }
}
```

### Return Format

Returns `TextContent` with:
- Success: stdout from `pdf_scraper.py`
- Failure: stderr + stdout for debugging

---

## Implementation

### MCP Server Changes

**Location:** `skill_seeker_mcp/server.py`

**Changes:**
1. Added `scrape_pdf` to `list_tools()` (lines 220-249)
2. Added handler in `call_tool()` (lines 276-277)
3. Implemented `scrape_pdf_tool()` function (lines 591-625)

### Code Implementation

```python
async def scrape_pdf_tool(args: dict) -> list[TextContent]:
    """Scrape PDF documentation and build skill (NEW in B1.7)"""
    config_path = args.get("config_path")
    pdf_path = args.get("pdf_path")
    name = args.get("name")
    description = args.get("description")
    from_json = args.get("from_json")

    # Build command
    cmd = [sys.executable, str(CLI_DIR / "pdf_scraper.py")]

    # Mode 1: Config file
    if config_path:
        cmd.extend(["--config", config_path])

    # Mode 2: Direct PDF
    elif pdf_path and name:
        cmd.extend(["--pdf", pdf_path, "--name", name])
        if description:
            cmd.extend(["--description", description])

    # Mode 3: From JSON
    elif from_json:
        cmd.extend(["--from-json", from_json])

    else:
        return [TextContent(type="text", text="❌ Error: Must specify --config, --pdf + --name, or --from-json")]

    # Run pdf_scraper.py
    result = subprocess.run(cmd, capture_output=True, text=True)

    if result.returncode == 0:
        return [TextContent(type="text", text=result.stdout)]
    else:
        return [TextContent(type="text", text=f"Error: {result.stderr}\n\n{result.stdout}")]
```

---

## Integration with MCP Workflow

### Complete Workflow Through MCP

```python
# 1. Create PDF config (optional - can use direct mode)
config_result = await mcp.call_tool("generate_config", {
    "name": "api_manual",
    "url": "N/A",  # Not used for PDF
    "description": "API Manual from PDF"
})

# 2. Scrape PDF
scrape_result = await mcp.call_tool("scrape_pdf", {
    "pdf_path": "docs/api_manual.pdf",
    "name": "api_manual",
    "description": "API Manual Documentation"
})

# 3. Package skill
package_result = await mcp.call_tool("package_skill", {
    "skill_dir": "output/api_manual/",
    "auto_upload": True  # Upload if ANTHROPIC_API_KEY set
})

# 4. Upload (if not auto-uploaded)
if "ANTHROPIC_API_KEY" in os.environ:
    upload_result = await mcp.call_tool("upload_skill", {
        "skill_zip": "output/api_manual.zip"
    })
```

### Combined with Web Scraping

```python
# Scrape web documentation
web_result = await mcp.call_tool("scrape_docs", {
    "config_path": "configs/framework.json"
})

# Scrape PDF supplement
pdf_result = await mcp.call_tool("scrape_pdf", {
    "pdf_path": "docs/framework_api.pdf",
    "name": "framework_pdf"
})

# Package both
await mcp.call_tool("package_skill", {"skill_dir": "output/framework/"})
await mcp.call_tool("package_skill", {"skill_dir": "output/framework_pdf/"})
```

---

## Error Handling

### Common Errors

**Error 1: Missing required parameters**
```
❌ Error: Must specify --config, --pdf + --name, or --from-json
```
**Solution:** Provide one of the three modes

**Error 2: PDF file not found**
```
Error: [Errno 2] No such file or directory: 'manual.pdf'
```
**Solution:** Check PDF path is correct

**Error 3: PyMuPDF not installed**
```
ERROR: PyMuPDF not installed
Install with: pip install PyMuPDF
```
**Solution:** Install PyMuPDF: `pip install PyMuPDF`

**Error 4: Invalid JSON config**
```
Error: json.decoder.JSONDecodeError: Expecting value: line 1 column 1
```
**Solution:** Check config file is valid JSON

---

## Testing

### Test MCP Tool

```bash
# 1. Start MCP server
python3 skill_seeker_mcp/server.py

# 2. Test with MCP client or via Claude Code

# 3. Verify tool is listed
# Should see "scrape_pdf" in available tools
```

### Test All Modes

**Mode 1: Config**
```python
result = await mcp.call_tool("scrape_pdf", {
    "config_path": "configs/example_pdf.json"
})
assert "✅ Skill built successfully" in result[0].text
```

**Mode 2: Direct**
```python
result = await mcp.call_tool("scrape_pdf", {
    "pdf_path": "test.pdf",
    "name": "test_skill"
})
assert "✅ Skill built successfully" in result[0].text
```

**Mode 3: From JSON**
```python
# First extract
subprocess.run(["python3", "cli/pdf_extractor_poc.py", "test.pdf", "-o", "test.json"])

# Then build via MCP
result = await mcp.call_tool("scrape_pdf", {
    "from_json": "test.json"
})
assert "✅ Skill built successfully" in result[0].text
```

---

## Comparison with Other MCP Tools

| Tool | Input | Output | Use Case |
|------|-------|--------|----------|
| `scrape_docs` | HTML URL | Skill | Web documentation |
| `scrape_pdf` | PDF file | Skill | PDF documentation |
| `generate_config` | URL | Config | Create web config |
| `package_skill` | Skill dir | .zip | Package for upload |
| `upload_skill` | .zip file | Upload | Send to Claude |

---

## Performance

### MCP Tool Overhead

- **MCP overhead:** ~50-100ms
- **Extraction time:** Same as CLI (15s-5m depending on PDF)
- **Building time:** Same as CLI (5s-45s)

**Total:** MCP adds negligible overhead (<1%)

### Async Execution

The MCP tool runs `pdf_scraper.py` synchronously via `subprocess.run()`. For long-running PDFs:
- Client waits for completion
- No progress updates during extraction
- Consider using `--from-json` mode for faster iteration

---

## Future Enhancements

### Potential Improvements

1. **Async Extraction**
   - Stream progress updates to client
   - Allow cancellation
   - Background processing

2. **Batch Processing**
   - Process multiple PDFs in parallel
   - Merge into single skill
   - Shared categories

3. **Enhanced Options**
   - Pass all extraction options through MCP
   - Dynamic quality threshold
   - Image filter controls

4. **Status Checking**
   - Query extraction status
   - Get progress percentage
   - Estimate time remaining

---

## Conclusion

Task B1.7 successfully implements:
- ✅ MCP tool `scrape_pdf`
- ✅ Three usage modes (config, direct, from-json)
- ✅ Integration with MCP server
- ✅ Error handling
- ✅ Compatible with existing MCP workflow

**Impact:**
- PDF scraping available through MCP
- Seamless integration with Claude Code
- Unified workflow for web + PDF documentation
- 10th MCP tool in Skill Seeker

**Total MCP Tools:** 10
1. generate_config
2. estimate_pages
3. scrape_docs
4. package_skill
5. upload_skill
6. list_configs
7. validate_config
8. split_config
9. generate_router
10. **scrape_pdf** (NEW)

---

**Task Completed:** October 21, 2025
**B1 Group Complete:** All 8 tasks (B1.1-B1.8) finished!

**Next:** Task group B2 (Microsoft Word .docx support)