Spatial clustering 2D grid reconstructor converting OCR boxes into Markdown tables
genpark-hybrid-bounding-box-ocr-table-reconstructor-skill is a deterministic, zero-dependency Python skill engineered with 100% production-grade functional parity for document layout parsing, complex financial/legal table reconstruction, formula consistency auditing, and sensitive PII redaction.
Executive Capability: Deterministic 2D bounding-box spatial clustering and table reconstruction engine recovering multi-column layouts, merged headers, and grid hierarchies.
pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.graph LR
User([π Document / Extracted OCR Payload]) -->|JSON-RPC Request| MCP[β‘ MCP Server / CLI]
MCP --> Client[π οΈ Document Skill Client]
Client --> Core[π§ Deterministic Spatial & Audit Kernel]
Core --> Output[π Structured Matrix & Validation Dossier]
Output --> User
python example_usage.py
from client import BoundingBoxTableReconstructor
client = BoundingBoxTableReconstructor()
result = client.run_benchmark_table_reconstruction()
print(result)
Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json{
"mcpServers": {
"genpark-hybrid-bounding-box-ocr-table-reconstructor-skill": {
"command": "python",
"args": ["/path/to/genpark-hybrid-bounding-box-ocr-table-reconstructor-skill/mcp_server.py"]
}
}
}
| Parameter | Type | Required | Description |
|---|---|---|---|
query_payload | string / dict | Yes | Primary document bounding box, table, financial, or text payload |
output_format | json / dict | Yes | Standardized response schema containing extracted matrices and audit telemetry |
GenPark AI Agent Skills are engineered with zero external dependencies using pure Python standard library code. This ensures maximum portability, instantaneous cold starts, and zero package version conflicts across diverse agent runtime environments.
Explore the comprehensive directory of open-source, production-ready AI Agent skills at the GenPark AI MCP Hub.
Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.
This listing does not have a supported local package template. Use the maintainerβs documentation for its hosted endpoint, authentication, and client-specific setup. No install command has been inferred.
https://github.com/Alpha-Park/genpark-hybrid-bounding-box-ocr-table-reconstructor-skill/releases/download/v1.0.1/genpark-ocr-table.mcpbotherGenPark Hybrid Bounding Box OCR Table Reconstructor works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.