# Spyglass AI MCP Server

> Use this tool when you need to analyze application performance and identify errors or bottlenecks, as it enables Large Language Models (LLMs) to query telemetry data and provide intelligent insights. It solves problems related to application optimization and troubleshooting by providing real-time data and analytics. The Spyglass AI MCP Server takes in telemetry data as input and outputs actionable insights, making it ideal for use cases where data-driven decision making is crucial.

Canonical page: https://skillsregistry.net/skills/spyglass-ai-spyglass-mcp  
JSON: https://api.skillsregistry.net/v1/skills/spyglass-ai-spyglass-mcp

## Description

Enables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/rw24i5spu8)
- **Repository:** <https://github.com/Spyglass-AI/spyglass-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": "spyglass-ai-spyglass-mcp"
    }
  }
}
```

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