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imnoo-team/drawing-converter-mcp

by Various

MCP server for converting technical drawings (PDF) and engineering callouts between metric and imperial — dimensions, fits, tolerances, threads, surface roughness.

MCP

imnoo-team/drawing-converter-mcp

Added 3 Sept 2026

#cnc #engineering #imperial #manufacturing #mcp #mcp-server #metric #model-context-protocol

Overview

MCP server that converts technical drawings in PDF format and engineering callouts between metric and imperial units. It handles dimensions, fits, tolerances, threads, and surface roughness. The project is distributed as a Dockerfile for deployment.

Best for

Best for
Engineers and developers needing automated metric-imperial conversion in technical drawings

Use cases

  • Convert PDF technical drawings between metric and imperial units
  • Translate engineering callouts for fits and tolerances
  • Process threads and surface roughness specifications in drawings

Notes

MCP server that converts technical drawings in PDF format and engineering callouts between metric and imperial units. It handles dimensions, fits, tolerances, threads, and surface roughness. The project is distributed as a Dockerfile for deployment.

0 stars on GitHub. Last updated 2026-08-03. Licensed MIT.

Use cases

  • Convert PDF technical drawings between metric and imperial units
  • Translate engineering callouts for fits and tolerances
  • Process threads and surface roughness specifications in drawings

Pros

  • Targets a specific engineering need not covered by generic converters
  • Uses MCP for integration with AI assistants and automation tools
  • Dockerfile simplifies deployment in containerized environments

Cons

  • No GitHub stars yet, indicating limited community validation
  • Only a Dockerfile is provided, requiring Docker to run
  • Input is limited to PDF drawings and engineering callouts

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Targets a specific engineering need not covered by generic converters
  • Uses MCP for integration with AI assistants and automation tools
  • Dockerfile simplifies deployment in containerized environments

Cons

  • No GitHub stars yet, indicating limited community validation
  • Only a Dockerfile is provided, requiring Docker to run
  • Input is limited to PDF drawings and engineering callouts
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