Agent-Ready with MCP Server

The Kipu Quantum Hub is now agent-ready, meaning you can access and manage your quantum computing resources directly through your favorite AI assistants like Claude, GitHub Copilot, and other AI-powered development tools. This opens up exciting new possibilities for working with quantum computing in a more natural, conversational way.

Imagine describing what you want to achieve in plain language and having your AI assistant handle the complexities of job submission, circuit optimization, and result analysis. Whether you're prototyping quantum algorithms, managing computational resources, or analyzing experimental results, your AI agent can now assist you every step of the way.

The Kipu Quantum Hub MCP Server

The Kipu Quantum Hub MCP Server (qhub-mcp) is a Model Context Protocol (MCP) server that bridges AI assistants with the Kipu Quantum Hub platform. MCP is an open standard that enables AI assistants to securely connect to external tools and data sources, extending their capabilities beyond conversation into real-world actions.

By installing the Kipu Quantum Hub MCP server, you give your AI assistant the ability to:

• Access your quantum resources — query available quantum hardware, check system status, and view your computational quotas
• Manage quantum jobs — submit, monitor, and retrieve results from quantum computations
• Work with quantum circuits — help you design, optimize, and execute quantum algorithms
• Streamline your workflow — handle routine tasks so you can focus on the science and innovation

The server exposes its capabilities as tools in two namespaces:

• hub_* — core Hub platform API (services, data pools, applications, use cases, …)
• quantum_* — Quantum Workloads API (quantum jobs, sessions, backends, …)

Plus a top-level run_subscribed_service tool to invoke services you are subscribed to.

Prerequisites

• Python 3.12 or higher
• uv (provides the uvx launcher)
• A valid Kipu Quantum Hub personal access token — use your default token or create a dedicated one in your account settings

Authentication

The server resolves credentials in the following order:

1. The KQH_PERSONAL_ACCESS_TOKEN environment variable.
2. Credentials stored by qhubctl after running qhubctl login -t <YOUR_PERSONAL_ACCESS_TOKEN>.

Logging in with qhubctl is the recommended setup for local use: the token lives in the CLI session instead of config files, and the CLI and MCP server stay in sync on a single access token.

Configure Your AI Agent

The server is launched via uvx qhub-mcp. You can provide your access token in one of two ways:

• Option A — with qhubctl (recommended): run qhubctl login -t <YOUR_PERSONAL_ACCESS_TOKEN> once, then use the client snippets below without an env block.
• Option B — inline token: add an env block to the server entry:

  "env": { "KQH_PERSONAL_ACCESS_TOKEN": "<YOUR_PERSONAL_ACCESS_TOKEN>" }

After updating any config file, restart your AI client to load the server.

Claude Desktop

Open Settings → Developer → Edit Config (this opens claude_desktop_config.json) and add:

{
  "mcpServers": {
    "qhub-mcp": {
      "command": "uvx",
      "args": [
        "qhub-mcp@latest"
      ]
    }
  }
}

Claude Code

Register the server with the CLI:

claude mcp add qhub-mcp -- uvx qhub-mcp@latest

Or add it manually to .mcp.json (per-project) or ~/.claude.json (global):

{
  "mcpServers": {
    "qhub-mcp": {
      "command": "uvx",
      "args": [
        "qhub-mcp@latest"
      ]
    }
  }
}

Cursor

Edit ~/.cursor/mcp.json (global) or .cursor/mcp.json (per-project):

{
  "mcpServers": {
    "qhub-mcp": {
      "command": "uvx",
      "args": [
        "qhub-mcp@latest"
      ]
    }
  }
}

VS Code

Add to your user or workspace settings.json (requires an MCP-capable extension such as GitHub Copilot Chat in agent mode):

{
  "mcp": {
    "servers": {
      "qhub-mcp": {
        "command": "uvx",
        "args": [
          "qhub-mcp@latest"
        ]
      }
    }
  }
}

Other MCP clients

Any MCP client that supports stdio servers can launch qhub-mcp with:

• command: uvx
• args: ["qhub-mcp@latest"]
• optional env: { "KQH_PERSONAL_ACCESS_TOKEN": "<TOKEN>", "QHUB_API_BASE_URL": "<URL>" }

What You Can Do

With the Kipu Quantum Hub MCP server connected to your AI assistant, you can:

Natural Language Quantum Computing

Describe what you want to accomplish in natural language, and your AI assistant will help translate that into quantum operations on the Kipu Quantum Hub.

Streamlined Workflows

• Quickly submit quantum jobs without context-switching between tools
• Monitor multiple jobs and get intelligent summaries of their status
• Retrieve and analyze results with AI-assisted interpretation

Intelligent Resource Management

• Ask about available quantum hardware and get recommendations
• Check your computational quotas and resource usage
• Plan and schedule quantum experiments efficiently

Development Assistance

• Get help designing quantum circuits with real-time feedback
• Debug quantum algorithms with AI-powered analysis
• Optimize circuits for specific quantum hardware architectures

Example Use Cases

"What quantum backends are currently available on the Kipu Quantum Hub? Which one would be best for a 20-qubit circuit?"

"I want to learn about use cases for quantum computing in finance. What use cases are described on the Kipu Quantum Hub?"

"Help me find suitable services on the Kipu Quantum Hub for my optimization problem."

"Retrieve the results from my last three quantum jobs and compare their results."

"How do I get started using Kipu's Illay Base Quantum Optimizer?"

Additional Resources

• PyPI Package: https://pypi.org/project/qhub-mcp/
• License: Apache License 2.0

Support

For issues, feature requests, or contributions, please visit the Discord Server and let us know.

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Ready to supercharge your quantum computing workflow with AI? Install the Kipu Quantum Hub MCP server and start exploring what's possible when you combine the power of quantum computing with intelligent assistance.