# component-mcp-server

> component-mcp-server — aniket-sharma27-component-mcp-server. Use this tool when you need to expose design system component documentation to large language models (LLMs) or integrate component information into AI workflows. It solves the problem of accessing and retrieving component contexts from Markdown files with YAML frontmatter, allowing for efficient listing and retrieval of design system components. The tool takes Markdown files as input and outputs component documentation via the MCP protocol, making it ideal for use cases that require programmatic access to design system information.

Canonical page: https://skillsregistry.net/skills/aniket-sharma27-component-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/aniket-sharma27-component-mcp-server

## Description

Exposes design system component documentation to LLM clients via MCP, allowing listing and retrieving component contexts from Markdown files with YAML frontmatter.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/nx7672ozpv)
- **Repository:** <https://github.com/Aniket-Sharma27/component-mcp-server>

## 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": "aniket-sharma27-component-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/aniket-sharma27-component-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/aniket-sharma27-component-mcp-server/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