The Trend Vision One Model Context Protocol (MCP) Server enables natural language interaction between your favourite AI tooling and the Trend Vision
Trend Vision One MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. The Trend Vision One Model Context Protocol (MCP) Server enables natural language interaction between your favourite AI tooling and the Trend Vision One web APIs. This allows users to harness the power of Large Language Models (LLM) to.
Once Trend Vision One is connected, these are the calls the assistant has available:
Prerequisites — The Prerequisites tool exposed by this serverWorkbench — The Workbench tool exposed by this serverSetup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
You will need one environment variable: TREND_VISION_ONE_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Trend Vision One's toolset — Prerequisites, Workbench — is a fair guide to whether it matches your workflow. It is maintained by trendmicro; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| Prerequisites | The Prerequisites tool exposed by this server. |
| Workbench | The Workbench tool exposed by this server. |
| Variable | Description | Required |
|---|---|---|
| TREND_VISION_ONE_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.