# Meta Ads Codex MCP

> Meta Ads Codex MCP — mariocodesforfun-meta-ads-codex-mcp. Use this tool when you need to analyze Meta Ads performance through conversational queries, as it provides read-only access to ad accounts, active ads, and performance summaries, helping to solve problems related to ad campaign optimization and performance monitoring. It takes conversational questions as input and outputs relevant performance data, making it ideal for use cases where quick and easy ad performance insights are required. Use it to streamline ad campaign analysis and inform data-driven decisions.

Canonical page: https://skillsregistry.net/skills/mariocodesforfun-meta-ads-codex-mcp  
JSON: https://api.skillsregistry.net/v1/skills/mariocodesforfun-meta-ads-codex-mcp

## Description

A local MCP server that lets Codex answer conversational questions about Meta Ads performance. It provides read-only tools for listing ad accounts, checking active ads, and summarizing account performance.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/f4eo2nnsyx)
- **Repository:** <https://github.com/mariocodesforfun/meta_ads_codex_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": "mariocodesforfun-meta-ads-codex-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mariocodesforfun-meta-ads-codex-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mariocodesforfun-meta-ads-codex-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