A Model Context Protocol (MCP) server and OpenAI function calling service for interacting with the Deriv API.
A Model Context Protocol (MCP) server and OpenAI function calling service for interacting with the Deriv API. The mcp deriv api server mcp server wraps that behind the Model Context Protocol, so an assistant can use it rather than through you.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
You will need one environment variable: DERIV_API_TOKEN. 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.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. It is maintained by raju-deriv; 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.
### For Docker Installation
```json
{
"mcpServers": {
"deriv-api-mcp": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"deriv-api-mcp"
]
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| DERIV_API_TOKEN | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
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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.