"General search for the term 'task'" matching MCP servers:

Translates natural language commands into structured geometric operations for a simulated CAD engine using LLMs. It enables users to create shapes, modify dimensions, and perform 3D operations like extrusion through the Model Context Protocol.

A Model Context Protocol (MCP) server that provides tools for interacting with OpenROAD and ORFS (OpenROAD Flow Scripts).

Enables LLMs to search and retrieve official Cisco network diagram icons as RGB PNG images, with metadata and category listing tools for building topology diagrams.

Model Context Protocol (MCP) server for @imqueue — lets AI coding agents (Claude Code, Cursor and others) search the docs, scaffold typed services & clients and use @imqueue/cli live.

AI-native architecture diagramming for MCP clients (Claude Code, Cursor, Windsurf). The calling agent authors the graph (nodes, groups, edges); Flowgraf validates it, lays it out deterministically with ELK, renders an SVG + Mermaid, and returns a link to a live, editable canvas you can refine by chat, drag, or one-click AI design review. Agent-authored ops — no API key and no LLM cost to the calle

An MCP server for Spec-Driven Development that transforms natural language ideas and meeting transcripts into structured, production-grade specifications using EARS notation. It automates a 7-phase pipeline to generate project artifacts like requirements, architecture designs, and task lists directly to disk.

An MCP server for querying and exploring SysML XMI models, specifically designed for MTConnect model exports. It allows users to search for packages, classes, and enumerations while providing tools for analyzing documentation and inheritance hierarchies.

Builds a semantic graph of codebases across 38 languages and exposes 42 MCP tools for structured code understanding, search, and impact analysis.

A local-first MCP server for macOS that enables AI assistants to read and manage Apple Calendar events via EventKit, with configurable permissions, audit logging, and a native setup app.

Provides tools for creating, deleting, and querying nodes and edges in Excalidraw diagrams, enabling diagram editing via LLM interfaces.

Provides a code graph querying and visualization MCP server, enabling users to search, trace, and describe code components, overlay diffs, and explore architecture through natural language.

An MCP server that integrates CST Studio Suite with the Model Context Protocol to enable automated electromagnetic simulation workflows. It provides specialized tools for material definition management and direct interaction with the CST Studio Suite environment.

A Model Context Protocol server for creating and managing draw.io diagrams with batch operations and rich node types.

MCP server for foldkit that exposes 7-prime spine, 7 κ-bands, and 6 fold operations as native tools and resources for use in MCP clients like Claude Code, enabling state folding, κ-band classification, and fold operations.

Provides comprehensive architectural expertise through specialized agents, resources, and tools for generating, evaluating, and modifying architectural designs.

An MCP server that enables natural language-driven creation and management of GNU Radio flowgraphs with validated block connections and parameter configurations. It provides tools for searching the GNU Radio block library, detecting SDR hardware, and generating functional signal processing code.

Enables creating and editing draw.io diagrams from structured descriptions, rendering them as interactive inline SVGs, and providing access to the full draw.io editor for further modification and export.

Enables autonomous software engineering workflows by routing intent to specialized modes, managing Fable5 task ledgers and backend contracts, auditing React/TypeScript stacks, generating architectural SVG diagrams, and enforcing write-guard path policies.

Generate Control System Architecture (CSA) diagrams using PlantUML via the Model Context Protocol (MCP). Supports ISA-95 Purdue model, industrial symbols, and multiple protocols.

Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.