# io.ignission/mcp

> Use this tool when you need to analyze TikTok video performance and develop a data-driven content strategy. It solves problems related to understanding audience engagement, tracking video metrics, and optimizing content for better reach and impact. The tool takes in TikTok video data as input and outputs actionable insights and recommendations for improving content strategy.

Canonical page: https://skillsregistry.net/skills/io-ignission-mcp  
JSON: https://api.skillsregistry.net/v1/skills/io-ignission-mcp

## Description

TikTok video data analytics and content strategy tools

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** social-media
- **Updated:** 2026-09-19

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.ignission%2Fmcp)
- **Repository:** <https://github.com/ignission-io/mcp>

## Use it

MCP endpoint published by the skill: `https://mcp.ignission.io/mcp`

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": "io-ignission-mcp"
    }
  }
}
```

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