"NVIDIA Isaac Sim Robotics Simulation Platform" matching MCP servers:

Enables natural language control of NVIDIA Isaac Sim through the Model Context Protocol, allowing you to create robots, build scenes, run simulations, and debug physics from any MCP-compatible IDE.

Lets AI agents drive a live, persistent Isaac Sim session: load any articulated robot from a USD plus JSON config, set normalized joint targets and named poses, tune gains and couplings live, run joint range tests, and capture screenshots. It also launches and monitors detached Isaac Lab training runs, with Kit kept up between calls so each experiment costs a frame instead of a full relaunch.

An MCP server that provides AI agents free access to NVIDIA's hosted AI models (100+ models) with automatic model routing for tasks like reasoning, coding, vision, embeddings, and translation.

Enables MCP-compatible assistants to inspect and diagnose NVIDIA Shield TV and Kodi over a local network, including redacted logs, playback and add-on checks, settings changes, reversible repairs, backups, and rollback. It runs locally and defaults to read-only until writes or plugin browsing are explicitly enabled.

Provides unified control for both physical robots (ROS-based like Moorebot Scout, Unitree) and virtual robots in Unity3D/VRChat, enabling multi-robot coordination, environment generation, and automated 3D model creation.

Provides a compressed knowledge graph of the NVIDIA AI developer stack for deterministic traversal, enabling agents to answer questions about dependencies and prerequisites with minimal tokens.

Enables building and evaluating shopping/support agents against a deterministic synthetic retail store with in-memory fixtures. Provides tools, resources, and prompts for product search, cart and order flows, inventory, and policy retrieval over stdio or Streamable HTTP.

Enables querying a compressed knowledge graph of the NVIDIA AI developer stack, allowing users to traverse declared dependencies, prerequisites, and relationships across 20 domains via read-only MCP tools like query_ckg, get_prerequisites, and search_concepts.

MCP server that integrates with the Cumulus Linux OS via NVUE API to read network configuration, interfaces, bridges, VRFs, BGP, and other network information.

Lets an AI assistant read and write business records in plain language, including looking up people, creating and updating tasks, logging time, and pulling utilization reports through a synthetic ops platform or an optional ClickUp adapter.

A read-only MCP server that enables AI agents to act as GCP platform engineers, allowing them to investigate incidents, take inventory, and find cost-optimization opportunities in Google Cloud projects without mutating any infrastructure.

This MCP server enables Claude Desktop to create, visualize, and simulate quantum circuits using Qiskit and Qiskit Aer, with support for preset circuits, custom QASM, and noise modeling.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

MCP server wrapping a mock internal ops platform (FastAPI + SQLite) so Claude Code can read and write employee, project, task, and time data through natural language.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

MCP server for Azure resource management, AI Foundry, and Entra ID — inspect and operate Azure infrastructure through AI agents.

Enables AI agents to interact with ServiceNow through MCP, providing schema inspection, record CRUD, attachments, audit, Flow Designer, and platform investigations with policy-guarded access.

Lets your coding agent talk to the RunWhen platform — workspace chat, issues, SLXs, run sessions, and the Tool Builder — over the Model Context Protocol. Enables workspace chat with AI assistant, task authoring via Tool Builder, and direct data access to workspaces, issues, SLXs, run sessions, and more.

Enables AI clients to call the documented APIs of real business platforms—job boards, freelance marketplaces, ad networks, e-commerce, messaging, social, sales, trading and market data—through a single CLI and runtime. Serves 455 catalogued platforms with one shared verb vocabulary per category, in both Python and TypeScript.

Enables MCP hosts like ChatGPT and Claude to query data platform metadata, explore schemas and tables, inspect SQL explain plans, and monitor DAG and ETL status through standardized tools.

About MCP server for Google Agent Platform Docs — Google AI + Vertex AI. 3400+ pages searchable by AI agents.

MCP server for grounded analysis of synthetic electric-taxi operations data, exposing tools for aggregated metrics, charging risk, and policy retrieval.

Connects AI assistants to ITM Platform for searching projects, inspecting budgets, creating tasks, logging risks and issues, and updating project details via natural language.

Governance proxy for MCP servers. Wraps any MCP server with policy evaluation, human approval workflows, and hash-chain audit trails. Supports stdio and Streamable HTTP transports.

Enables AI assistants to manage Sciple platform content including environments, services, dashboards, runbooks, projects, and tickets through the Sciple REST API.

Enables authenticated clients to discover and call tools for scoped file listing/searching, request client-side LLM sampling, and receive real-time progress/log notifications over stdio or secure Streamable HTTP, with tenant/user workspace isolation and a loopback browser dashboard.

Enables natural language conversion of production and queueing systems into Petri net models, with simulation and PNML export via MCP tools.

Bootstrap MCP server for future data exploration and querying across multiple databases, currently only provides a hello_world tool with no actual data connectivity.

Enables AI assistants to drive a locally running desktop fire-simulation app through natural language — opening projects, recognizing drawings, building geometry and meshes, running fire/smoke, evacuation, HVAC smoke-control and sprinkler water-spray hydraulics analyses, and reviewing ASET/RSET results. Ships an ontology, rule set, glossaries and step-by-step playbooks so prompts stay accurate and errors are caught before a run.

Enables AI assistants to control NVIDIA Isaac Sim by building scenes, loading assets, operating robots and humans, reading sensors, managing simulation, and creating Action Graphs.