🚀 Marketing MCP Servers Suite

A comprehensive collection of MCP (Model Context Protocol) servers designed for modern marketing teams, enabling AI-powered automation across all marketing channels.

📦 Included Servers

1. Social Media MCP Server

Manage multi-platform social media campaigns with AI-powered optimization.

• Platforms: Twitter/X, LinkedIn, Instagram, Facebook, TikTok
• Features: Scheduling, analytics, hashtag optimization, media handling
• AI Tools: Content generation, best time posting, engagement prediction

2. Analytics MCP Server

Unified analytics across all marketing channels.

• Integrations: Google Analytics, social platforms, email tools
• Features: ROI tracking, attribution, custom dashboards
• AI Tools: Predictive analytics, anomaly detection, insights

3. Content Management MCP Server

AI-powered content creation and management.

• Features: Content generation, brand voice, version control
• Storage: Local/cloud, organized libraries
• AI Tools: Writing assistance, tone checking, optimization

4. Email Marketing MCP Server

Sophisticated email campaign automation.

• Features: List management, segmentation, A/B testing
• Platforms: SendGrid, Mailchimp, custom SMTP
• AI Tools: Subject line optimization, personalization

5. SEO Tools MCP Server

Comprehensive SEO optimization and monitoring.

• Features: Keyword research, technical SEO, backlinks
• Integrations: Google Search Console, SEMrush APIs
• AI Tools: Content optimization, SERP prediction

🚀 Quick Start

1. Clone and Install

git clone https://github.com/yourusername/marketing-mcp-servers.git
cd marketing-mcp-servers
./setup.sh

2. Configure API Keys

cp .env.template .env
# Edit .env with your API credentials

3. Add to MCP Client

The setup script generates mcp-config.json. Add it to your MCP client:

{
  "mcpServers": {
    "social-media": {
      "command": "python3",
      "args": ["-m", "social_media_mcp"],
      "env": { "SOCIAL_API_KEYS": "path/to/keys" }
    },
    "analytics": {
      "command": "python3",
      "args": ["-m", "analytics_mcp"],
      "env": { "ANALYTICS_CONFIG": "path/to/config" }
    }
    // ... other servers
  }
}

💡 Example Workflows

Multi-Channel Campaign

# 1. Generate content ideas
ideas = await mcp.call_tool("content", "generate_ideas", {
    "topic": "product launch",
    "channels": ["social", "email", "blog"]
})

# 2. Create content
content = await mcp.call_tool("content", "create_content", {
    "ideas": ideas,
    "brand_voice": "professional yet friendly"
})

# 3. Schedule social posts
await mcp.call_tool("social-media", "schedule_campaign", {
    "content": content.social_posts,
    "platforms": ["twitter", "linkedin"],
    "optimize_timing": true
})

# 4. Launch email campaign
await mcp.call_tool("email", "create_campaign", {
    "content": content.email,
    "list": "subscribers",
    "schedule": "optimal"
})

# 5. Monitor performance
report = await mcp.call_tool("analytics", "track_campaign", {
    "campaign_id": "launch_2024",
    "metrics": ["engagement", "conversions", "roi"]
})

SEO-Optimized Content

# 1. Research keywords
keywords = await mcp.call_tool("seo", "keyword_research", {
    "topic": "AI marketing tools",
    "intent": "informational"
})

# 2. Generate optimized content
article = await mcp.call_tool("content", "create_seo_content", {
    "keywords": keywords,
    "length": 2000,
    "format": "blog_post"
})

# 3. Technical optimization
optimized = await mcp.call_tool("seo", "optimize_content", {
    "content": article,
    "target_keywords": keywords.primary
})

# 4. Publish and track
await mcp.call_tool("content", "publish", {
    "content": optimized,
    "monitor_rankings": true
})

🏗️ Architecture

graph TB
    subgraph "MCP Servers"
        SM[Social Media MCP]
        AN[Analytics MCP]
        CM[Content MCP]
        EM[Email MCP]
        SEO[SEO MCP]
    end
    
    subgraph "External APIs"
        TW[Twitter API]
        LI[LinkedIn API]
        GA[Google Analytics]
        SG[SendGrid]
        GSC[Search Console]
    end
    
    subgraph "AI Models"
        GPT[GPT-4]
        CLAUDE[Claude]
        LOCAL[Local Models]
    end
    
    SM --> TW
    SM --> LI
    AN --> GA
    EM --> SG
    SEO --> GSC
    
    CM --> GPT
    CM --> CLAUDE
    SEO --> LOCAL

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🔧 Integration with A2A Marketing Suite

These MCP servers are designed to work seamlessly with the A2A Marketing Suite:

1. Creative Director Agent can call any MCP server for data
2. Content Agent uses the Content MCP for generation
3. Analytics Agent pulls from Analytics MCP
4. Distribution Agent uses Social Media and Email MCPs

# A2A Agent using MCP
class ContentAgent(A2AAgent):
    async def create_content(self, brief):
        # Use Content MCP
        content = await self.mcp_client.call_tool(
            "content", 
            "generate_content",
            {"brief": brief}
        )
        return content

📊 Features Matrix

Server	Content Gen	Analytics	Scheduling	AI-Powered	Multi-Platform
Social Media	✅	✅	✅	✅	✅
Analytics	❌	✅	❌	✅	✅
Content	✅	✅	❌	✅	✅
Email	✅	✅	✅	✅	❌
SEO	✅	✅	❌	✅	❌

🚦 Status

• ✅ Social Media MCP - Ready
• ✅ Analytics MCP - Ready
• ✅ Content MCP - Ready
• ✅ Email MCP - Ready
• ✅ SEO MCP - Ready

🤝 Contributing

See CONTRIBUTING.md for guidelines.

📄 License

MIT License - see LICENSE for details.