Synter-Media-AI/mcp-server

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

How to use

Install

npx @synterai/mcp-server

Tools exposed

• list_campaigns
• create_search_campaign
• create_display_campaign
• create_pmax_campaign
• create_meta_campaign
• create_linkedin_campaign
• create_reddit_campaign
• pause_campaign
• update_campaign_budget
• get_performance
• get_daily_spend
• add_keywords
• add_negative_keywords
• create_conversion
• list_conversions
• diagnose_tracking
• generate_image
• generate_video
• upload_image
• list_ad_accounts

Tested with

Claude Desktop, Cursor, Amp, ChatGPT

Example client config

{\n  "mcpServers": {\n    "synter": {\n      "command": "npx",\n      "args": ["@synterai/mcp-server"],\n      "env": {\n        "SYNTER_API_KEY": "syn_your_api_key_here"\n      }\n    }\n  }\n}

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.