Module 10: Real-World MCP Use Cases

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Putting It All Together

Throughout this course, you've learned MCP concepts, configuration, and development. Now let's see how these pieces combine into practical, real-world solutions. These use cases demonstrate the power of MCP and should inspire ideas for your own implementations.

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Use Case 1: Development Workflow Assistant

Scenario: A development team wants Claude to assist with their daily workflow - understanding the codebase, reviewing changes, and helping with documentation.

Configuration:

{
  "mcpServers": {
    "project-code": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem",
               "./src", "./tests", "./docs"]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": {
        "GITHUB_PERSONAL_ACCESS_TOKEN": "${GITHUB_TOKEN}"
      }
    },
    "project-db": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres"],
      "env": {
        "DATABASE_URL": "${DEV_DATABASE_URL}"
      }
    }
  }
}

Enabled Workflows:

1. Code Review

   • "Review the changes in the latest PR for security issues"
   • Claude reads the PR diff, analyzes code, and provides feedback

2. Documentation Updates

   • "Update the API documentation based on the current routes"
   • Claude reads route files and updates docs accordingly

3. Database Schema Understanding

   • "What tables are related to user authentication?"
   • Claude queries schema and explains relationships

4. Bug Investigation

   • "The user login is failing - check the auth module and recent commits"
   • Claude examines code, git history, and suggests fixes

---

Use Case 2: Research and Content Creation

Scenario: A content creator needs help researching topics and gathering information from multiple sources.

Configuration:

{
  "mcpServers": {
    "web-search": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-brave-search"],
      "env": {
        "BRAVE_API_KEY": "${BRAVE_API_KEY}"
      }
    },
    "web-fetch": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-fetch"]
    },
    "notes": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem",
               "~/Research", "~/Drafts"]
    },
    "memory": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-memory"]
    }
  }
}

Enabled Workflows:

1. Topic Research

   • "Research the latest developments in quantum computing"
   • Claude searches, reads articles, and synthesizes findings

2. Fact Checking

   • "Verify the statistics in my draft about climate change"
   • Claude searches for authoritative sources and validates claims

3. Content Organization

   • "Organize my research notes on AI ethics into an outline"
   • Claude reads notes folder and creates structured outline

4. Persistent Context

   • "Remember that I'm writing an article series on renewable energy"
   • Claude stores context and references it in future sessions

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Use Case 3: Data Analysis Pipeline

Scenario: A data analyst needs to query databases, analyze results, and generate reports.

Configuration:

{
  "mcpServers": {
    "analytics-db": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres"],
      "env": {
        "DATABASE_URL": "${ANALYTICS_DATABASE_URL}"
      }
    },
    "reports": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem",
               "~/Reports", "~/Data"]
    }
  }
}

Enabled Workflows:

1. Ad-hoc Analysis

   • "What were our top 10 products by revenue last month?"
   • Claude queries database and presents formatted results

2. Trend Investigation

   • "Analyze the user signup trend over the past 6 months"
   • Claude runs queries, identifies patterns, and explains findings

3. Report Generation

   • "Create a weekly sales summary report"
   • Claude queries data and generates markdown report

4. Data Quality Checks

   • "Find any orders with missing customer information"
   • Claude runs validation queries and reports issues

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Use Case 4: DevOps Monitoring Assistant

Scenario: An operations team wants Claude to help monitor systems and troubleshoot issues.

Custom Server Implementation:

// monitoring-server.ts
const server = new Server(
  { name: "monitoring-server", version: "1.0.0" },
  { capabilities: { tools: {}, resources: {} } }
);

// Resources for current status
server.setRequestHandler(ListResourcesRequestSchema, async () => ({
  resources: [
    {
      uri: "metrics://cpu",
      name: "CPU Metrics",
      description: "Current CPU usage across all servers"
    },
    {
      uri: "metrics://memory",
      name: "Memory Metrics",
      description: "Current memory usage across all servers"
    },
    {
      uri: "alerts://active",
      name: "Active Alerts",
      description: "Currently firing alerts"
    }
  ]
}));

// Tools for actions
server.setRequestHandler(ListToolsRequestSchema, async () => ({
  tools: [
    {
      name: "get_server_logs",
      description: "Retrieve recent logs from a specific server",
      inputSchema: {
        type: "object",
        properties: {
          server: { type: "string", description: "Server hostname" },
          lines: { type: "number", description: "Number of log lines" },
          level: { type: "string", enum: ["error", "warn", "info", "debug"] }
        },
        required: ["server"]
      }
    },
    {
      name: "check_service_status",
      description: "Check if a service is running on a server",
      inputSchema: {
        type: "object",
        properties: {
          server: { type: "string" },
          service: { type: "string" }
        },
        required: ["server", "service"]
      }
    }
  ]
}));

Enabled Workflows:

1. Alert Investigation

   • "We got a memory alert on prod-web-01, what's happening?"
   • Claude checks metrics, reads logs, and identifies the cause

2. Health Checks

   • "Verify all production services are running correctly"
   • Claude checks each service and reports status

3. Log Analysis

   • "Find any errors in the API logs in the last hour"
   • Claude retrieves and analyzes log entries

4. Incident Support

   • "Users are reporting slow page loads"
   • Claude investigates metrics, logs, and suggests remediations

---

Use Case 5: Customer Support Knowledge Base

Scenario: A support team wants Claude to access their knowledge base and help resolve customer issues.

Custom Server Implementation:

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

server.setRequestHandler(ListToolsRequestSchema, async () => ({
  tools: [
    {
      name: "search_knowledge_base",
      description: "Search the support knowledge base for articles",
      inputSchema: {
        type: "object",
        properties: {
          query: { type: "string", description: "Search query" },
          category: {
            type: "string",
            enum: ["billing", "technical", "account", "general"]
          }
        },
        required: ["query"]
      }
    },
    {
      name: "get_customer_info",
      description: "Retrieve customer account information (non-sensitive)",
      inputSchema: {
        type: "object",
        properties: {
          customerId: { type: "string" }
        },
        required: ["customerId"]
      }
    },
    {
      name: "log_interaction",
      description: "Log a customer support interaction",
      inputSchema: {
        type: "object",
        properties: {
          customerId: { type: "string" },
          category: { type: "string" },
          summary: { type: "string" },
          resolution: { type: "string" }
        },
        required: ["customerId", "category", "summary"]
      }
    }
  ]
}));

Enabled Workflows:

1. Issue Resolution

   • "Customer can't reset their password - find relevant KB articles"
   • Claude searches knowledge base and provides step-by-step solution

2. Account Lookup

   • "Look up account status for customer ID 12345"
   • Claude retrieves (non-sensitive) account info for context

3. Documentation

   • "Log this interaction: billing question about recurring charges"
   • Claude creates appropriate interaction record

---

Use Case 6: Content Management System

Scenario: A marketing team wants Claude to help manage their blog and social media content.

Configuration with Custom Server:

{
  "mcpServers": {
    "content-files": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem",
               "./content", "./drafts", "./published"]
    },
    "cms-api": {
      "command": "node",
      "args": ["./cms-server/dist/index.js"],
      "env": {
        "CMS_API_KEY": "${CMS_API_KEY}"
      }
    },
    "image-assets": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem",
               "./assets/images"]
    }
  }
}

CMS Server Tools:

tools: [
  {
    name: "publish_post",
    description: "Publish a draft post to the live site",
    inputSchema: { ... }
  },
  {
    name: "schedule_post",
    description: "Schedule a post for future publication",
    inputSchema: { ... }
  },
  {
    name: "get_analytics",
    description: "Get performance metrics for published content",
    inputSchema: { ... }
  }
]

Enabled Workflows:

1. Content Creation

   • "Draft a blog post about our new feature launch"
   • Claude creates draft in the content folder

2. Editorial Review

   • "Review the draft in drafts/feature-launch.md for SEO"
   • Claude reads and suggests improvements

3. Publishing

   • "Schedule this post for next Tuesday at 10 AM"
   • Claude schedules via CMS API

4. Performance Review

   • "Which posts performed best this month?"
   • Claude retrieves analytics and provides insights

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Use Case 7: Learning and Education Platform

Scenario: An educational institution wants Claude to help students with course materials and assignments.

Configuration:

{
  "mcpServers": {
    "course-materials": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem",
               "./courses", "./syllabus", "./resources"]
    },
    "student-progress": {
      "command": "node",
      "args": ["./education-server/dist/index.js"],
      "env": {
        "EDUCATION_DB_URL": "${EDUCATION_DB_URL}"
      }
    }
  }
}

Enabled Workflows:

1. Material Lookup

   • "Find the reading materials for Chapter 5 of the algorithms course"
   • Claude navigates course structure and provides materials

2. Concept Explanation

   • "Explain quicksort using examples from the course materials"
   • Claude reads relevant materials and provides explanation

3. Progress Tracking

   • "What assignments are due this week for CS101?"
   • Claude checks syllabus and due dates

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Building Your Own Use Case

When designing your MCP implementation:

1. Identify the pain points

• What tasks are repetitive?
• Where does context-switching waste time?
• What information is hard to access?

2. Map to MCP primitives

• Resources: What data should Claude read?
• Tools: What actions should Claude take?
• Prompts: What standardized workflows are needed?

3. Plan the configuration

• Which existing servers can you use?
• What custom servers are needed?
• What permissions are appropriate?

4. Start simple, iterate

• Begin with one or two servers
• Add more as needs become clear
• Refine based on actual usage

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Key Takeaways

1. MCP enables powerful workflows - The combination of servers creates capabilities greater than the sum of parts

2. Use existing servers - Many needs are covered by official and community servers

3. Custom servers unlock unique value - Your specific systems and data can become AI-accessible

4. Security must be considered - Each use case has specific permission requirements

5. Start with your actual needs - The best implementations solve real problems

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Conclusion

These use cases demonstrate MCP's potential, but they're just the beginning. As the ecosystem grows and more servers become available, new possibilities will emerge. The foundation you've built in this course positions you to take advantage of these opportunities.

Think about your own work:

• What systems do you access daily?
• What tasks could benefit from AI assistance?
• What integrations would make you more effective?

The answers to these questions are your roadmap for MCP implementation.

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Next up: Course Conclusion - The Future of AI Integration