# JAOT MCP Server

> Use this tool when you need to leverage optimization solver tools for natural language problem solving, enabling AI agents to find optimal solutions to complex problems. It exposes solver tools via the Model Context Protocol, allowing for seamless integration with AI systems. Ideal for use cases requiring automated decision-making, resource allocation, and constraint optimization.

Canonical page: https://skillsregistry.net/skills/avallavall-jaot  
JSON: https://api.skillsregistry.net/v1/skills/avallavall-jaot

## Description

Exposes optimization solver tools to AI agents via the Model Context Protocol, enabling natural language problem solving.

## Trust

- **Trust score (0–1):** 0.29
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/lblr8sa1i1)
- **Repository:** <https://github.com/avallavall/jaot>

## 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": "avallavall-jaot"
    }
  }
}
```

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