vibe-coding-cn/libs/external/Skill_Seekers-development/docs/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

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

Example config (configs/manual_pdf.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

# 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

# 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

{
  "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

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

# 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

# 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

# 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

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

Mode 2: Direct

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

# 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)

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

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