# spark-mcp

> Use this tool when you need to analyze Spark Desktop meeting transcripts and emails using natural language queries, enabling efficient search and insight generation through the Model Context Protocol, which takes in natural language inputs and returns relevant transcript and email data as output, ideal for use cases requiring quick information retrieval and context-based analysis.

Canonical page: https://skillsregistry.net/skills/feamster-spark-mcp  
JSON: https://api.skillsregistry.net/v1/skills/feamster-spark-mcp

## Description

Enables users to access, search, and analyze Spark Desktop meeting transcripts and emails through natural language via the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.66
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fk74j9vtd9)
- **Repository:** <https://github.com/feamster/spark-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": "feamster-spark-mcp"
    }
  }
}
```

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