by pipeboard-co
Optimize Facebook ad campaigns with AI-driven insights, creative analysis, and campaign control in Meta Ads Manager for
Provides AI-driven analysis and management of Meta advertising campaigns across Facebook and Instagram. Lets you retrieve performance data, visualize ad creatives, and get strategic recommendations through natural language queries.
Meta Ads is a community-built MCP server published by pipeboard-co that provides AI assistants with tools and capabilities via the Model Context Protocol. Optimize Facebook ad campaigns with AI-driven insights, creative analysis, and campaign control in Meta Ads Manager for It is categorized under developer tools, analytics data.
You can install Meta Ads in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.
NOASSERTION
Meta Ads is released under the NOASSERTION license.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Useful MCP listing: Meta Ads is the kind of server we cite when onboarding engineers to host + tool permissions.
According to our notes, Meta Ads benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
We evaluated Meta Ads against two servers with overlapping tools; this profile had the clearer scope statement.
We wired Meta Ads into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Meta Ads reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Meta Ads for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Useful MCP listing: Meta Ads is the kind of server we cite when onboarding engineers to host + tool permissions.
Meta Ads is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Meta Ads has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Meta Ads surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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A Model Context Protocol (MCP) server for interacting with Meta Ads. Analyze, manage and optimize Meta advertising campaigns through an AI interface. Use an LLM to retrieve performance data, visualize ad creatives, and provide strategic insights for your ads on Facebook, Instagram, and other Meta platforms.
DISCLAIMER: This is an unofficial third-party tool and is not associated with, endorsed by, or affiliated with Meta in any way. This project is maintained independently and uses Meta's public APIs according to their terms of service. Meta, Facebook, Instagram, and other Meta brand names are trademarks of their respective owners.
mcp-name: co.pipeboard/meta-ads-mcp
The fastest and most reliable way to get started is to 🚀 Get started with our Meta Ads Remote MCP. Our cloud service uses streamable HTTP transport for reliable, scalable access to Meta Ads data. No technical setup required - just connect and start analyzing your ad campaigns with AI!
https://mcp.pipeboard.co/meta-ads-mcpThat's it! You can now ask Claude to analyze your Meta ad campaigns, get performance insights, and manage your advertising.
For direct token-based authentication without the interactive flow, use this URL format when adding the integration:
https://mcp.pipeboard.co/meta-ads-mcp?token=YOUR_PIPEBOARD_TOKEN
Get your token at pipeboard.co/api-tokens.
Add the following to your ~/.cursor/mcp.json. Once you enable the remote MCP, click on "Needs login" to finish the login process.
{
"mcpServers": {
"meta-ads-remote": {
"url": "https://mcp.pipeboard.co/meta-ads-mcp"
}
}
}
If you prefer to authenticate without the interactive login flow, you can include your Pipeboard API token directly in the URL:
{
"mcpServers": {
"meta-ads-remote": {
"url": "https://mcp.pipeboard.co/meta-ads-mcp?token=YOUR_PIPEBOARD_TOKEN"
}
}
}
Get your token at pipeboard.co/api-tokens.
Use the Remote MCP URL: https://mcp.pipeboard.co/meta-ads-mcp
📖 Get detailed setup instructions for your AI client here
For MCP clients that support token-based authentication, you can append your Pipeboard API token to the URL:
https://mcp.pipeboard.co/meta-ads-mcp?token=YOUR_PIPEBOARD_TOKEN
This bypasses the interactive login flow and authenticates immediately. Get your token at pipeboard.co/api-tokens.
🚀 We strongly recommend using Remote MCP instead - it's faster, more reliable, and requires no technical setup.
Meta Ads MCP also supports a local streamable HTTP transport, allowing you to run it as a standalone HTTP API for web applications and custom integrations. See Streamable HTTP Setup Guide for complete instructions.
✨ Get started with Remote MCP here - no technical setup required! Just connect your Facebook Ads account and start asking AI to analyze your campaigns.
For advanced users who need to self-host, the package can be installed from source. Local installations require creating your own Meta Developer App. We recommend using Remote MCP for a simpler experience.
mcp_meta_ads_get_ad_accounts
access_token (optional): Meta API access token (will use cached token if not provided)user_id: Meta user ID or "me" for the current userlimit: Maximum number of accounts to return (default: 200)mcp_meta_ads_get_account_info
access_token (optional): Meta API access token (will use cached token if not provided)account_id: Meta Ads account ID (format: act_XXXXXXXXX)mcp_meta_ads_get_account_pages
access_token (optional): Meta API access token (will use cached token if not provided)account_id: Meta Ads account ID (format: act_XXXXXXXXX) or "me" for the current user's pagesmcp_meta_ads_get_campaigns
access_token (optional): Meta API access token (will use cached token if not provided)account_id: Meta Ads account ID (format: act_XXXXXXXXX)limit: Maximum number of campaigns to return (default: 10)status_filter: Filter by status (empty for all, or 'ACTIVE', 'PAUSED', etc.)mcp_meta_ads_get_campaign_details
access_token (optional): Meta API access token (will use cached token if not provided)campaign_id: Meta Ads campaign IDmcp_meta_ads_create_campaign
access_token (optional): Meta API access token (will use cached token if not provided)
account_id: Meta Ads account ID (format: act_XXXXXXXXX)
name: Campaign name
objective: Campaign objective (ODAX, outcome-based). Must be one of:
OUTCOME_AWARENESSOUTCOME_TRAFFICOUTCOME_ENGAGEMENTOUTCOME_LEADSOUTCOME_SALESOUTCOME_APP_PROMOTIONNote: Legacy objectives such as BRAND_AWARENESS, LINK_CLICKS, CONVERSIONS, APP_INSTALLS, etc. are no longer valid for new campaigns and will cause a 400 error. Use the outcome-based values above. Common mappings:
BRAND_AWARENESS → OUTCOME_AWARENESSREACH → OUTCOME_AWARENESSLINK_CLICKS, TRAFFIC → OUTCOME_TRAFFICPOST_ENGAGEMENT, PAGE_LIKES, EVENT_RESPONSES, VIDEO_VIEWS → OUTCOME_ENGAGEMENTLEAD_GENERATION → OUTCOME_LEADSCONVERSIONS, CATALOG_SALES, MESSAGES (sales-focused flows) → OUTCOME_SALESAPP_INSTALLS → OUTCOME_APP_PROMOTIONstatus: Initial campaign status (default: PAUSED)
special_ad_categories: List of special ad categories if applicable
daily_budget: Daily budget in account currency (in cents)
lifetime_budget: Lifetime budget in account currency (in cents)
bid_strategy: Bid strategy. Must be one of: LOWEST_COST_WITHOUT_CAP, LOWEST_COST_WITH_BID_CAP, COST_CAP, LOWEST_COST_WITH_MIN_ROAS.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.