"SearXNG - Open Source Metasearch Engine" matching MCP servers:

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

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.

Enables AI agents to search, read, organize, draft, send, and schedule email through a scoped token, with actions journaled and reversible. It also supports proposal queues, approval workflows, and undo operations for safe mailbox automation.

MCP server that integrates SearXNG search into n8n workflows. Enables AI agents to perform web searches using configurable parameters and multiple search engines.

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

Enables AI-driven creation of savable Wallpaper Engine web wallpaper source projects through a local STDIO service, with bounded project discovery, revision-checked file edits, checkpoint restore, validation, and publish staging. It also opens managed preview windows to set public properties and capture screenshots and bounded logs as runtime feedback from the official engine.

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

A Model Context Protocol (MCP) server that enables AI assistants to interact with Camunda Platform workflow engine. Provides 21 specialized tools for complete workflow automation and process management.

MCP server for governed AI content publishing to platforms like WeChat, Juejin, CSDN, and Zhihu, exposing tools for platform auth checks, content preflight, publish job lifecycle, verification, and liveness monitoring.

A deterministic MCP server that executes 10-step topology pipelines on Cloudflare Workers, providing structured progress snapshots and adaptive JSON templates for AI agents.

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.

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.

A local MCP server that uses Word COM automation to perform tasks python-docx cannot, such as computing field/TOC values, counting real pages, rendering high-fidelity PDFs, converting/repairing legacy formats, producing redline comparisons, and running native mail merge.

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.

Enables real Excel desktop automation to recalculate formulas, read computed cell values, and export true-fidelity PDFs, complementing library-based workflows.

Enables AI assistants to control and automate Unreal Engine through a native C++ Automation Bridge plugin. It supports a comprehensive range of tasks including asset management, actor manipulation, editor control, and blueprint graph editing.

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 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.