# indigo-mcp

> indigo-mcp — richard-ni-indigo-mcp. Use this tool when you need to automate astronomy equipment control through natural language, enabling seamless interaction with telescopes, cameras, and other observatory devices. It solves problems of manual equipment operation and complex scripting, providing a user-friendly interface for AI agents to send commands and receive status updates. Ideal for astronomy applications requiring automated equipment control and monitoring.

Canonical page: https://skillsregistry.net/skills/richard-ni-indigo-mcp  
JSON: https://api.skillsregistry.net/v1/skills/richard-ni-indigo-mcp

## Description

MCP server for the INDIGO astronomy automation protocol, enabling AI agents to control telescopes, cameras, focusers, filter wheels, domes, and other observatory equipment through natural language.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/yk3belp1he)
- **Repository:** <https://github.com/Richard-Ni/indigo-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": "richard-ni-indigo-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/richard-ni-indigo-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/richard-ni-indigo-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