"A tool or system to control 3D modelers" matching MCP servers:

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables AI-driven 3D model generation and manipulation using OpenSCAD through natural language commands. Users can create primitives, apply transformations, perform boolean operations, and export models to various formats like STL and OBJ.

MCP server for generating print-ready 3D models from text descriptions via a multi-agent pipeline, enabling AI assistants to create and optimize STL files.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

Governance framework for LLM agents. Exposes seven mechanically-enforced rules plus tools for preflight file protection, audit-chain verification, session handoff and worklog templates, MCP config auditing, and an emergency kill switch.

An MCP server that exposes 218 Blender tools for full 3D modeling pipelines, with a LangGraph agent layer for planning, executing, observing, and reviewing modeling tasks with evidence-based verification.

A server built on mcp-framework that enables integration with Claude Desktop through the Model Context Protocol.

A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.

Enables users to deploy a production-grade control plane for agents, providing a spec-compliant MCP server, scoped tool grants, failure-mode detection, and cost governance.

Serves a loopback-only MCP endpoint that lets a same-machine client start, steer, and cancel DSH Sessions it knows by id, list their durable subagent trees, deliver messages to continuable children, and read durable event logs with paging and chunked oversized-event recovery. It maps every call onto native Session Controller and subagent services without owning task state, starting a second listener, or registering model-facing tools.

MCP server that gives Claude Code full mouse, keyboard, and app control on macOS. Tell Claude what to do and watch it operate your computer.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables coding agents to request, track, and verify independent cross-model reviews with structured findings, attachment hashes, and provenance receipts via Chrome Bridge, Codex, or Responses transports.

Enables one coding agent to inspect, configure, debug, and repair another agent over stdio MCP, with redacted reads and confirm-gated writes and restarts.

Enables reviewing and dispatching existing Codex tasks across projects through a lightweight control panel, including scanning task inventories, confirming Continue or Optimize prompts, and tracking dispatch progress.

A framework for building hot-loadable MCP tools that feature conversational negotiation, graduated permissions, and zero-downtime updates. It enables persistent state continuity across server restarts and provides a hypothetical evaluation system for tool actions.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Provides a no-op 'think' tool that enables Claude to decompose complex problems and enhance reasoning by pausing to organize thoughts.