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Synter-Media-AI/mcp-server

by Various

MCP server for AI agents to manage ad campaigns across Google, Meta, LinkedIn, Microsoft, Reddit, TikTok, and more

S

MCP

Synter-Media-AI/mcp-server

Added 1 June 2026

Overview

An open-source MCP server that lets AI agents manage ad campaigns across Google, Meta, LinkedIn, Microsoft, Reddit, TikTok, and other platforms. Built in JavaScript, it exposes a set of tools via the Model Context Protocol for programmatic campaign creation, bidding, and reporting.

Best for

Best for
Developers building AI agents that need to automate multi-platform ad campaign management

Use cases

  • Automating cross-platform ad campaign creation and optimization
  • Integrating ad platform APIs into AI agent workflows
  • Programmatic bidding and performance monitoring across multiple ad networks

Notes

An open-source MCP server that lets AI agents manage ad campaigns across Google, Meta, LinkedIn, Microsoft, Reddit, TikTok, and other platforms. Built in JavaScript, it exposes a set of tools via the Model Context Protocol for programmatic campaign creation, bidding, and reporting.

11 stars on GitHub. Last updated 2026-05-27. Licensed MIT.

Use cases

  • Automating cross-platform ad campaign creation and optimization
  • Integrating ad platform APIs into AI agent workflows
  • Programmatic bidding and performance monitoring across multiple ad networks

Pros

  • Supports a wide range of major ad platforms out of the box
  • Leverages the standard MCP protocol for easy integration with AI agents
  • Open source and free to self-host

Cons

  • Very early stage with only 11 GitHub stars and limited community adoption
  • Requires self-hosting and managing API credentials for each platform
  • Documentation and examples are sparse, making setup more challenging

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Supports a wide range of major ad platforms out of the box
  • Leverages the standard MCP protocol for easy integration with AI agents
  • Open source and free to self-host

Cons

  • Very early stage with only 11 GitHub stars and limited community adoption
  • Requires self-hosting and managing API credentials for each platform
  • Documentation and examples are sparse, making setup more challenging