"Autogenerating toolpaths in Mastercam CAM software" matching MCP servers:

Enables AI agents to safely inspect, edit, and test code within a bounded repository environment to solve software engineering tasks and verify fixes.

MCP bridge for Distill — let Claude, Cursor, or any MCP client rename files based on AI content analysis. 9 tools for renaming, suggestions (preview), folder watching, history, and rule management. Five AI providers: Claude, OpenAI GPT-4o, Gemini, Ollama (local), Apple Intelligence. Bridge open-source (MIT), Distill app is commercial (pay-per-use, no subscription).

A security-first MCP server that provides LLMs with structured tools for filesystem, process, search, build/test/lint, IDE integration, and more.

A local-first MCP server that gives AI coding assistants persistent, structured, human-readable memory for a software project by storing project knowledge as Markdown files in the project's .dev-context-memory/ folder.

MCP server for TQS structural engineering CAD/analysis software, enabling Claude to read building models, extract drawing data, run structural processing, and script against the TQS API.

Enables Windows program management through MCP, including listing installed programs, uninstalling software, force removal, and cleaning residual files. Supports generating detailed Markdown reports of system programs with smart categorization and statistics.

A local Windows automation MCP server that lets a KI-Agent safely control the SteuerSparErklärung tax software: inventory and open tax cases, read pages, compare receipts and values, and edit verified working copies, with all ELSTER transmission paths locked tight.

A Windows MCP server that gives ChatGPT permission-controlled tools for troubleshooting software, working with files, running diagnostics, and operating the visible desktop.

Enables reading, searching, editing, and writing files in legacy encodings such as GBK, Big5, Shift-JIS, and Windows codepages, with automatic detection and preservation of the original encoding.

Enables LLMs to discover, read, and edit tables in HTML/Markdown documents by converting messy collapsed HTML into clean pipe format and writing back with version-checked, surgical cell, row, and column operations.

MCP server that gives AI chat real vision by reading images, files, logs, and zip archives via local OCR in any language, with privacy-first processing.

Enables AI agents to inspect and work with PDF files entirely on the local machine, covering page counts, metadata, layout, encryption permissions, scan-vs-text detection, and page rendering. Generated results land in a temporary workspace as short artifact ids that can be chained between tools and exported to real folders on request.

Enables AI assistants to inspect, create, and report on IFC/BIM files locally, and to open models in a viewer with BCF viewpoint support.

An MCP server for creating named checkpoints and snapshots of projects, with selective file restore, content diffs, and artifact preservation, enabling safe recovery from external file changes in Claude Code.

Enables read-only scanning and text extraction from PDF, DOCX, PPTX, SVG, and PNG files in a local folder, providing the raw text to AI models for summarization or analysis without an external LLM API.

Integrates CopyQ clipboard manager with LLM agents, enabling reading, writing, searching, and managing clipboard items organized in tabs with tags and notes through a unified interface.

Policy layer for multi-agent workspaces: one JSON policy file decides what each path is worth; agents can audit, explain and dry-run clean plans themselves, nothing is ever deleted by pattern, and every action lands in a hash-chained journal. Zero dependencies; pip install workspace-metabolism then wm mcp.

Enables AI coding agents to persist structured long-term memory (gotchas, architecture, API notes) in a .context folder and sync across devices and agents via Git.

Convert technical-drawing PDFs and engineering callouts between metric and imperial — values stamped in place, threads cross-referenced, shop-floor rounding.

Enables AI agents to read and edit Word (.docx) and PDF documents with byte-level fidelity, using minimal in-package rewrites for DOCX and text-layer detection with page rendering for PDF, including OCR-free handling of scanned files via image output.