# isingq-mcp

> isingq-mcp — ising-tech-isingq-toolkit. Use this tool when you need to model complex optimization problems as Quadratic Unconstrained Binary Optimization (QUBO) and solve them efficiently via the IsingQ cloud, with local validation and user confirmation to ensure accurate results. It takes optimization problems as input and outputs solutions, providing a reliable interface for solving challenging problems. Ideal for use cases requiring advanced optimization techniques, such as logistics, finance, and energy management.

Canonical page: https://skillsregistry.net/skills/ising-tech-isingq-toolkit  
JSON: https://api.skillsregistry.net/v1/skills/ising-tech-isingq-toolkit

## Description

MCP server for modeling optimization problems as QUBO and solving them via IsingQ cloud with local validation and user confirmation.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/rd0ny61oq6)
- **Repository:** <https://github.com/ising-tech/isingq-toolkit>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ising-tech-isingq-toolkit"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ising-tech-isingq-toolkit` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ising-tech-isingq-toolkit/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt