"Headroom open-notebook resources" matching MCP servers:

Provides tools for interacting with Jupyter notebooks, allowing users to read, add, and execute notebook cells. It supports full notebook execution and metadata retrieval through the FastMCP framework.

Enables AI agents to manage Splitwise expenses through natural language, including reading balances, splitting costs, and handling authentication and rate limits automatically.

Fill standard legal agreement templates (NDAs, SAFEs, NVCA docs, employment, cloud terms) and produce DOCX files.

Enables reading and editing nTop notebook block graphs, running them headlessly through nTop Automate, and measuring the resulting geometry.

Enables AI assistants to manage Open Tracked containers and Google Tag Manager, including domains, tracking scores, power-ups, and one-request GTM pack installation.

Exposes open automation platform capabilities to AI agents with tools for managing job templates, inventories, collections, EDA activations, audit events, and policy checks, governed by gateway auth, RBAC, and policy enforcement.

An MCP server for mobile automation that enables LLMs to interact with Android and iOS devices through screenshot, tap, swipe, log analysis, and app lifecycle management.

A modular productivity automation server providing reusable prompt templates, composable skills, and multi-step workflows for tasks like daily planning, code review, document summarization, and project management.

An open-source Model Context Protocol application management platform that allows users to create applications from GitHub repositories with automatic information extraction and database integration.

Local-first MCP runtime for fast, reversible, template-aware Excel automation, enabling agents to manipulate live Excel workbooks with safety features like snapshots and rollbacks.

Enables AI agents to automate both web browsers and native desktop applications through a unified interface, supporting tasks like browsing, clicking, typing, and file clipboard operations via exposed MCP tools.

A server that integrates Blender with local AI models via the Model Context Protocol, allowing users to control Blender using natural language prompts for 3D modeling tasks.

Enables control of Open Brush 3D painting software through natural language commands, allowing LLMs to create drawings, manipulate brushes, import 3D models, manage colors, layers, and camera settings via the Open Brush HTTP API.

Enables AI clients to prepare and preview labels, then safely submit physical print jobs to an Xprinter XP-330B through local stdio or authenticated remote access, with status, cancellation, and retry receipts.

Lets AI agents see and control desktop applications through the accessibility layer, enabling clicking, typing, scrolling, dragging, and window/app management across macOS, Windows, and Linux entirely on the local machine.

A Model Context Protocol server for comprehensive Jupyter notebook manipulation, featuring position-based cell operations and bulk editing. It includes specialized integration for VS Code to synchronize notebook changes and trigger file reloads.

Enables AI agents to control a live Blender session over the Model Context Protocol, creating, modifying, and inspecting scene objects, applying materials, rendering images, and pulling PolyHaven assets. Prompts can be routed through a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, or Azure) that is configurable at startup or swappable at runtime.

Enables AI agents to control a live Blender session over MCP, creating and modifying objects, applying materials, rendering images, and downloading PolyHaven assets. It also routes prompts to a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be listed and switched at runtime.

Enables AI agents to control a live Blender session, including scene and object operations, rendering, and PolyHaven asset workflows. Supports provider-agnostic LLM backends that can be switched at runtime through MCP tools.

Enables AI agents to drive a live Blender session over MCP — inspecting scenes, creating and modifying objects, applying materials, rendering, and pulling PolyHaven assets — while routing natural-language prompts through a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible endpoints, or Azure) that can be switched at runtime.

Enables AI agents to control a live Blender session through MCP tools for scene and object manipulation, rendering, PolyHaven asset search/download/texturing, and guided scene workflows, while allowing runtime switching between local or OpenAI-compatible LLM providers.

Enables AI agents to control a live Blender session through MCP tools for scene inspection, object creation and editing, rendering, and PolyHaven asset management, while supporting provider-agnostic LLM backends that can be switched at runtime.

Enables AI agents to control a live Blender session through tools for scene and object manipulation, rendering, PolyHaven asset access, and guided prompts. It supports switching between provider-agnostic LLM backends such as Ollama, LM Studio, llama.cpp, and OpenAI-compatible endpoints.

Enables AI assistants to manage Joplin Notes through the Web Clipper API, supporting note creation, updates, search, notebook organization, and tag management.

Enables AI agents to control a live Blender session by creating, modifying, rendering, and managing scene objects, textures, and PolyHaven assets through MCP tools. It also routes prompts across configurable local or OpenAI-compatible LLM backends that can be switched at runtime.

Enables AI agents to drive a live Blender session through MCP tools for scene and object control, rendering, and PolyHaven asset download. It is provider-agnostic, letting users send prompts to and switch between Ollama, LM Studio, llama.cpp, OpenAI, and other OpenAI-compatible backends at runtime.

Enables AI agents to control a live Blender session over the Model Context Protocol, exposing tools for scene and object manipulation, rendering, code execution, and PolyHaven asset downloading. It also routes prompts to a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, or Azure) that can be switched at runtime.

Enables AI agents to control a live Blender session through MCP, including scene and object manipulation, rendering, PolyHaven asset integration, and runtime-switchable LLM backends.

Enables AI agents to drive a live Blender session over MCP — inspecting and creating scene objects, applying materials, rendering, executing code, and fetching PolyHaven assets. It also exposes prompt, provider, and model tools backed by a provider-agnostic LLM layer (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be switched at runtime.

An MCP server that connects to the Resource Hub, allowing centralized configuration and management of tools and resources across different MCP environments.