MCP Server Integration: Connect ACOS to Everything

How I extended Claude's capabilities with browser automation, image generation, and custom APIs.

TL;DR

Model Context Protocol (MCP) is the standard for connecting Claude to external tools. ACOS includes 7 MCP servers: Browser (Playwright), Memory (Knowledge Graph), Sequential Thinking, Lyric Genius, Nano Banana (images), and custom Creator/Database servers. This guide covers how each works, when to use them, and how to build your own MCP server in 30 minutes.

What Is Model Context Protocol (MCP)?

MCP is Anthropic's open standard for connecting AI models to external capabilities. Think of it as USB for AI—a universal way to plug in new tools.

Without MCP:

Claude → Limited to text generation
         Can't browse web
         Can't access databases
         Can't generate images
         Can't run code

With MCP:

Claude → MCP Server → Browser (Playwright)
      → MCP Server → Database (PostgreSQL)
      → MCP Server → Image Generator (Gemini)
      → MCP Server → Any API you build

Why MCP Matters for Creators

The 7 MCP Servers in ACOS

ACOS ships with 7 MCP server integrations:

1. Browser (Playwright)

What It Does: Full browser automation—navigate, click, screenshot, fill forms, extract data.

When to Use:

• Research that requires browsing multiple pages
• Testing web applications
• Scraping structured data
• Taking screenshots for documentation

Example:

/acos "Take a screenshot of the ACOS GitHub repo README"

# Claude will:
# 1. Open browser via Playwright MCP
# 2. Navigate to github.com/frankxai/agentic-creator-os
# 3. Take screenshot
# 4. Return image in conversation

Key Tools:

2. Memory (Knowledge Graph)

What It Does: Persistent knowledge storage across sessions. Entities, relationships, observations.

When to Use:

• Storing information about projects
• Building knowledge bases
• Remembering user preferences
• Tracking relationships between concepts

Example:

/acos "Remember that the ACOS project uses 7 pillars architecture"

# Claude will:
# 1. Create entity: "ACOS"
# 2. Create entity: "7 Pillars Architecture"
# 3. Create relation: ACOS -> uses -> 7 Pillars
# 4. Persist for future sessions

Key Tools:

3. Sequential Thinking

What It Does: Extended reasoning for complex problems. Chain-of-thought with revision.

When to Use:

• Multi-step problem solving
• Complex analysis
• When you need Claude to "think harder"
• Debugging intricate issues

Example:

/council "Should I pivot my product strategy?"

# The Sequential Thinking MCP enables:
# 1. Break problem into components
# 2. Analyze each component
# 3. Revise reasoning based on new insights
# 4. Synthesize final recommendation

Key Tools:

4. Lyric Genius

What It Does: Advanced prompt engineering for Suno AI music generation.

When to Use:

• Creating music with specific styles
• Genre-bending compositions
• Lyric writing with techniques
• Music prompt optimization

Example:

/create-music "Epic orchestral piece about coding at midnight"

# Lyric Genius MCP provides:
# 1. Genre-specific vocabulary
# 2. Structural templates
# 3. Rhyme scheme suggestions
# 4. Emotional arc guidance

Key Tools:

5. Nano Banana (Image Generation)

What It Does: Generate and edit images using Gemini's image model.

When to Use:

• Hero images for blog posts
• Social media graphics
• Concept visualization
• Infographics and diagrams

Example:

/infogenius "Create architecture diagram for microservices"

# Nano Banana MCP:
# 1. Constructs optimized prompt
# 2. Calls Gemini image API
# 3. Returns high-res PNG
# 4. Includes grounding for accuracy

Key Tools:

6. Creator (Social APIs)

What It Does: Connect to social platforms for publishing and analytics.

Capabilities:

• LinkedIn posting
• Twitter/X threads
• Instagram scheduling
• Analytics retrieval

Note: Requires API credentials configuration.

7. Database (Content Storage)

What It Does: Persistent content storage for articles, tracks, and inventory.

Capabilities:

• Store article drafts
• Track music catalog
• Manage content inventory
• Query historical content

How MCP Architecture Works

The Communication Pattern

MCP Server Anatomy

Every MCP server has three components:

// 1. TOOLS - What actions the server can perform
{
  name: "browser_navigate",
  description: "Navigate to a URL",
  parameters: {
    url: { type: "string", required: true }
  }
}

// 2. RESOURCES - Data the server exposes
{
  uri: "browser://current-page",
  description: "The current page state"
}

// 3. TRANSPORT - How Claude communicates
// Options: stdio, HTTP, WebSocket

How to Build Your Own MCP Server

Step 1: Create the Project

mkdir my-mcp-server
cd my-mcp-server
npm init -y
npm install @modelcontextprotocol/sdk

Step 2: Define Your Tools

// src/index.ts
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const server = new Server(
  {
    name: "my-custom-server",
    version: "1.0.0",
  },
  {
    capabilities: {
      tools: {},
    },
  },
);

// Define a tool
server.setRequestHandler("tools/list", async () => ({
  tools: [
    {
      name: "my_custom_tool",
      description: "Does something useful",
      inputSchema: {
        type: "object",
        properties: {
          input: { type: "string", description: "The input" },
        },
        required: ["input"],
      },
    },
  ],
}));

// Handle tool calls
server.setRequestHandler("tools/call", async (request) => {
  if (request.params.name === "my_custom_tool") {
    const { input } = request.params.arguments;
    // Your logic here
    return {
      content: [{ type: "text", text: `Processed: ${input}` }],
    };
  }
});

// Start server
const transport = new StdioServerTransport();
await server.connect(transport);

Step 3: Configure in Claude Code

// ~/.claude/settings.json
{
  "mcpServers": {
    "my-custom-server": {
      "command": "node",
      "args": ["/path/to/my-mcp-server/dist/index.js"]
    }
  }
}

Step 4: Test It

# Build
npm run build

# Restart Claude Code
claude

# Use your tool
"Use my_custom_tool with input 'hello world'"

Real-World MCP Integration Examples

Example 1: Research Pipeline with Browser

/research "Latest Claude Code features 2026"

# MCP Flow:
# 1. Browser MCP → Navigate to anthropic.com
# 2. Browser MCP → Extract feature list
# 3. Browser MCP → Navigate to GitHub releases
# 4. Browser MCP → Extract changelog
# 5. Memory MCP → Store findings
# 6. Return synthesized research

Example 2: Content Creation with Multiple MCPs

/factory "Blog post about MCP integration"

# MCP Flow:
# 1. Browser MCP → Research current MCP docs
# 2. Memory MCP → Recall previous MCP knowledge
# 3. Sequential Thinking → Structure article
# 4. (Writing happens in Claude)
# 5. Nano Banana MCP → Generate hero image
# 6. Memory MCP → Store article metadata

Example 3: Music Production Pipeline

/create-music "Synthwave track about AI consciousness"

# MCP Flow:
# 1. Lyric Genius MCP → Get synthwave conventions
# 2. Lyric Genius MCP → Generate creative constraints
# 3. Lyric Genius MCP → Compose optimized prompt
# 4. (User takes prompt to Suno)
# 5. Nano Banana MCP → Generate album art
# 6. Memory MCP → Add to music inventory

MCP Best Practices

When to Use Which MCP

Performance Tips

1. Batch browser operations — Multiple navigations are slow; plan your path
2. Cache in Memory MCP — Don't research the same thing twice
3. Use Sequential Thinking sparingly — It's powerful but token-heavy
4. Optimize image prompts — Better prompts = fewer regenerations

Security Considerations

1. API keys in environment — Never in code
2. Sandbox browser sessions — Don't log into sensitive accounts
3. Validate MCP server sources — Only install trusted servers
4. Audit custom servers — Review code before deployment

Troubleshooting MCP Issues

Server Not Connecting

# Check if server is running
ps aux | grep mcp

# Verify config path
cat ~/.claude/settings.json

# Test server directly
node /path/to/server/dist/index.js

Tool Not Available

# List available tools
/mcp-status

# Check server capabilities
# Server may not expose the tool you expect

Slow Performance

1. Browser MCP — Consider headless mode
2. Memory MCP — Prune old entities periodically
3. Image generation — Use appropriate resolution

Frequently Asked Questions

What is MCP in Claude Code?

Model Context Protocol (MCP) is Anthropic's standard for connecting Claude to external tools and data sources. It enables capabilities like web browsing, image generation, and database access.

How many MCP servers can I run?

There's no hard limit, but each server consumes resources. ACOS typically runs 5-7 servers simultaneously without issues.

Can I build MCP servers in Python?

Yes, the MCP SDK supports both TypeScript and Python. The patterns are similar.

Do MCP servers persist between sessions?

The servers themselves restart with Claude Code. However, Memory MCP persists data to disk, surviving restarts.

Are MCP servers secure?

MCP servers run locally with your permissions. They can access what you can access. Be cautious with untrusted servers.

How do I update an MCP server?

Pull the latest code, rebuild, and restart Claude Code. No special migration needed for most updates.

Can MCP servers communicate with each other?

Not directly through MCP. However, Claude can orchestrate multiple servers, passing data between them in the conversation.

Next Steps

1. Explore existing servers — Try each of the 7 ACOS MCP servers
2. Build a simple server — Follow the guide above
3. Integrate your APIs — Connect your own services
4. Share with community — Contribute useful servers back

Related Articles

• The Complete Guide to Agentic Creator OS v6
• Building Custom Skills for ACOS
• Swarm Intelligence: Multi-Agent Orchestration

MCP — The universal connector for AI capabilities.

MCP Specification | GitHub | FrankX