# Shadow Complement Integration MCP

> Use this tool when you need to add psychological depth to visual compositions by integrating Jungian shadow principles. It solves problems of visual flatness and lack of emotional resonance by applying systematic visual opposition after multi-domain blending. The tool takes unified composition parameters as input and outputs a more nuanced and engaging visual representation.

Canonical page: https://skillsregistry.net/skills/dmarsters-shadow-complement-mcp  
JSON: https://api.skillsregistry.net/v1/skills/dmarsters-shadow-complement-mcp

## Description

Applies Jungian shadow complement to unified composition parameters, creating psychological depth through systematic visual opposition after multi-domain blending.

## 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:** api-integration
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/g5un9wnv4b)
- **Repository:** <https://github.com/dmarsters/shadow-complement-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": "dmarsters-shadow-complement-mcp"
    }
  }
}
```

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