# decimalai-mcp

> decimalai-mcp — decimal-labs-decimalai-mcp. Use this tool when you need to efficiently search and rank AI skills based on their measured effectiveness, solving problems of skill discovery and optimization. It provides a server interface for the DecimalAI skills registry, accepting queries and returning ranked results. Ideal for use cases where skill selection and prioritization are critical, such as AI model development and deployment.

Canonical page: https://skillsregistry.net/skills/decimal-labs-decimalai-mcp  
JSON: https://api.skillsregistry.net/v1/skills/decimal-labs-decimalai-mcp

## Description

MCP server for the DecimalAI skills registry — skill search ranked by measured effectiveness

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/decimal-labs/decimalai-mcp)

## 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": "decimal-labs-decimalai-mcp"
    }
  }
}
```

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