# Fully Sovereign AI Workflow

This use case shows how to keep an AI-assisted IONOS CLOUD workflow entirely within EU infrastructure: from the prompt you type, through inference, to the API calls the assistant makes on your behalf.

## Why a sovereign path

A standard MCP setup splits responsibility across two boundaries:

* The **MCP server** runs locally and calls the <code class="expression">space.vars.ionos\_cloud\_api</code> directly. That traffic stays inside the EU.
* The **AI client** sends your prompts and the JSON returned by MCP tools to its model backend. For Claude Desktop, Cursor, or VS Code Copilot, that backend sits outside the EU.

For workloads where resource names, IP addresses, billing figures, or audit-log entries must not leave EU jurisdiction (regulated industries, public sector, contractual data-residency commitments), replace the non-EU model backend with the [<mark style="color:blue;">IONOS CLOUD AI Model Hub</mark>](/cloud/ai/ai-model-hub.md). Inference then runs on open-weight LLMs hosted in IONOS's German data centers, and no component of the round trip crosses the EU boundary.

## Architecture

```mermaid
flowchart LR
    subgraph workstation["Your workstation (EU)"]
        client["AI Client\n(OpenAI-compatible)"]
        server["IONOS CLOUD MCP Server\nLocal binary"]
        client <-->|"MCP / JSON-RPC"| server
    end

    subgraph ionos["IONOS CLOUD (German data centers)"]
        api["IONOS CLOUD API"]
        hub["IONOS CLOUD AI Model Hub\nMistral · Llama · GPT-OSS"]
    end

    server <-->|"HTTPS"| api
    client <-->|"OpenAI-compatible HTTPS"| hub
```

Every endpoint in this diagram is operated by IONOS in Germany. No prompt, tool output, or API request reaches a non-EU AI provider in the request path.

{% hint style="info" %}
**Note:** Sovereignty applies to the data plane shown above. AI clients may still emit telemetry, crash reports, or autocomplete suggestions to their vendor backend independently of the configured inference endpoint; disable client telemetry if this matters for your compliance posture.
{% endhint %}

## What you need

* The `ionoscloud-mcp` binary. For more information, see [<mark style="color:blue;">Quick Start</mark>](/cloud/ai/mcp-server/quick-start.md).
* An <code class="expression">space.vars.ionos\_cloud\_api</code> token scoped to the products you intend to inspect. For more information, see [<mark style="color:blue;">Authentication</mark>](/cloud/ai/mcp-server/configuration/authentication.md).
* Access to the [<mark style="color:blue;">IONOS CLOUD AI Model Hub</mark>](/cloud/ai/ai-model-hub.md) with a token for its OpenAI-compatible endpoint.
* An AI client that supports both **MCP** *and* a **custom OpenAI-compatible base URL**. The MCP server is client-agnostic, but the AI client itself must let you redirect inference away from the vendor default. Options that meet both criteria today include [<mark style="color:blue;">Continue</mark>](/cloud/ai/mcp-server/connect-to-an-ai-client/continue.md), [<mark style="color:blue;">OpenCode</mark>](/cloud/ai/mcp-server/connect-to-an-ai-client/opencode.md), and clients built on the OpenAI Agents SDK. See each client's documentation for the exact provider-override setting.

## Choose a model

The AI Model Hub serves several open-weight LLMs that support tool calling, a prerequisite for MCP. Reasonable starting points:

| Model             | Good for                                                   |
| ----------------- | ---------------------------------------------------------- |
| Mistral Small 24B | General infrastructure Q\&A, fast responses                |
| Llama 3.3 70B     | Multi-step agentic workflows, larger context               |
| GPT-OSS 120B      | The most capable open model, when latency is less critical |

For more information, see [<mark style="color:blue;">Models Comparison</mark>](/cloud/ai/ai-model-hub/models/models-comparison.md) for the full list, context windows, and tool-calling support.

## Configure the client

Point your AI client at two things: the IONOS CLOUD AI Model Hub for inference, and the local MCP binary for tools.

1. In the client's model/provider settings, set the **base URL** to the AI Model Hub OpenAI-compatible endpoint and provide your Model Hub API token. For more information, see [<mark style="color:blue;">AI Model Hub API</mark>](/cloud/ai/ai-model-hub.md) for the exact URL and authentication flow.
2. In the client's MCP settings, add the `ionoscloud` server entry exactly as shown in the per-client guide (for example, [<mark style="color:blue;">Continue</mark>](/cloud/ai/mcp-server/connect-to-an-ai-client/continue.md#add-the-mcp-server) or [<mark style="color:blue;">OpenCode</mark>](/cloud/ai/mcp-server/connect-to-an-ai-client/opencode.md#add-the-mcp-server)).
3. Restart the client so it picks up both the new provider and the MCP server.

## Verify the sovereign path

Ask the assistant a question that requires a tool call:

> *List my* <code class="expression">space.vars.ionos\_cloud</code> *data centers and summarise them.*

If the response includes your real data centers, both halves are wired correctly: the MCP server reached the IONOS CLOUD API for the list, and the Model Hub model produced the summary. Confirm in the client's logs that requests went to your configured Model Hub base URL rather than the vendor default.

## Limitations to be aware of

* **Open-weight models trail frontier models on complex agentic chains.** For deep multi-step reasoning across dozens of tool calls, expect to iterate more than you would with a frontier closed model. Start with concrete, narrowly scoped prompts.
* **Not every MCP-capable AI client allows a custom inference endpoint.** Vendor-locked clients (Claude Desktop, Cursor) currently route inference to their own backend and cannot be redirected to the AI Model Hub. Choose the client based on this constraint, not just on MCP support.
* **Sovereignty is end-to-end.** If you later add a third MCP server that calls a non-EU SaaS, that traffic leaves the perimeter; the IONOS-side guarantees apply only to the IONOS CLOUD MCP server and the AI Model Hub.

## Related topics

* [<mark style="color:blue;">Data sovereignty</mark>](/cloud/ai/mcp-server/overview.md#data-sovereignty)
* [<mark style="color:blue;">Does the MCP server send my data to Anthropic or other AI providers?</mark>](/cloud/ai/mcp-server/faq.md#does-the-mcp-server-send-my-data-to-anthropic-or-other-ai-providers)
* [<mark style="color:blue;">Composing Multiple MCP Servers</mark>](/cloud/ai/mcp-server/use-cases/agentic-workflows.md#composing-multiple-mcp-servers)


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