# MCP-ORTools

> Use this tool when you need to solve complex constraint satisfaction and optimization problems, such as resource allocation or scheduling, by submitting JSON model specifications to Google OR-Tools. It enables Large Language Models to leverage OR-Tools' capabilities, providing outputs in the form of optimized solutions. Ideal for use cases requiring efficient problem-solving, such as logistics, finance, or supply chain management.

Canonical page: https://skillsregistry.net/skills/mcp-reasoner-mcp-reasoner  
JSON: https://api.skillsregistry.net/v1/skills/mcp-reasoner-mcp-reasoner

## Description

Enables Large Language Models to submit and solve constraint satisfaction and optimization problems using Google OR-Tools through JSON model specification.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/uk39wmzyic)
- **Repository:** <https://github.com/MCP-Reasoner/MCP-Reasoner>

## 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": "mcp-reasoner-mcp-reasoner"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mcp-reasoner-mcp-reasoner` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mcp-reasoner-mcp-reasoner/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