# Stelar Signals MCP

> Stelar Signals MCP — stelardigital-stelar-signals-mcp. Use this tool when you need to analyze and make informed decisions in the crypto market, as it provides access to a range of signals including regime, sentiment, price, and risk. The Stelar Signals MCP tool solves problems related to market trend identification, risk assessment, and data interpretation, offering outputs such as summarized market insights and fact-checked information. It is ideal for use in applications where real-time market data analysis is crucial, with inputs including raw market data and outputs comprising actionable signals and insights.

Canonical page: https://skillsregistry.net/skills/stelardigital-stelar-signals-mcp  
JSON: https://api.skillsregistry.net/v1/skills/stelardigital-stelar-signals-mcp

## Description

Enables AI agents to access crypto market signals including regime, sentiment, price, risk, and text tools like summarization and fact-checking, backed by a live production-grade classifier.

## 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:** finance
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wmq3udvy1j)
- **Repository:** <https://github.com/StelarDigital/stelar-signals-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": "stelardigital-stelar-signals-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/stelardigital-stelar-signals-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/stelardigital-stelar-signals-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