# multidim-mcp

> multidim-mcp — cherridsaid-multidim-mcp. Use this tool when you need to perform consistent multi-lens analysis without relying on network calls or model inference. The multidim-mcp provides deterministic structured thinking grids and validation, enabling AI agents to analyze complex data from multiple perspectives. It is ideal for use cases requiring reliable and efficient decision-making, with inputs of complex data and outputs of validated analysis grids.

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

## Description

Provides deterministic structured thinking grids and validation for AI agents, enabling consistent multi-lens analysis without network calls or model inference.

## Trust

- **Trust score (0–1):** 0.51
- **Verification tier:** scanned
- **Last scanned:** 2026-09-04

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-04

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/u2kwgghvjm)
- **Repository:** <https://github.com/Cherridsaid/multidim-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": "cherridsaid-multidim-mcp"
    }
  }
}
```

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