Tutorial 3: MCP Integration

Add external tools to your LLM application via Model Context Protocol.

Time: 30 minutes
Level: Intermediate

What You’ll Build

A chatbot that can read and manipulate files using MCP filesystem tools.

What You’ll Learn

• Set up MCP servers
• Register external tools
• Enable automatic tool calling
• Handle tool execution
• Build tool-enabled agents

Prerequisites

• Completed Tutorial 2
• Node.js (for MCP servers)

Step 1: Install MCP Filesystem Server

The filesystem server provides file operations as tools:

# Test the MCP server
npx -y @modelcontextprotocol/server-filesystem /tmp/allowed

This starts an MCP server that can access files in /tmp/allowed.

Step 2: Create Tool-Enabled Bot

package main

import (
    "bufio"
    "context"
    "fmt"
    "log"
    "os"
    "strings"

    "github.com/AltairaLabs/PromptKit/runtime/mcp"
    "github.com/AltairaLabs/PromptKit/runtime/pipeline"
    "github.com/AltairaLabs/PromptKit/runtime/pipeline/middleware"
    "github.com/AltairaLabs/PromptKit/runtime/providers/openai"
    "github.com/AltairaLabs/PromptKit/runtime/tools"
)

func main() {
    // Create MCP registry
    mcpRegistry := mcp.NewRegistry()
    defer mcpRegistry.Close()

    // Register filesystem server
    err := mcpRegistry.RegisterServer(mcp.ServerConfig{
        Name:    "filesystem",
        Command: "npx",
        Args:    []string{"-y", "@modelcontextprotocol/server-filesystem", "/tmp/allowed"},
    })
    if err != nil {
        log.Fatal(err)
    }

    // Create tool registry
    toolRegistry := tools.NewRegistry()
    toolRegistry.RegisterExecutor(tools.NewMCPExecutor(mcpRegistry))

    // Discover and register MCP tools
    ctx := context.Background()
    serverTools, err := mcpRegistry.ListAllTools(ctx)
    if err != nil {
        log.Fatal(err)
    }

    for _, mcpTools := range serverTools {
        for _, mcpTool := range mcpTools {
            toolRegistry.Register(&tools.ToolDescriptor{
                Name:        mcpTool.Name,
                Description: mcpTool.Description,
                InputSchema: mcpTool.InputSchema,
                Mode:        "mcp",
            })
            fmt.Printf("Registered tool: %s\n", mcpTool.Name)
        }
    }

    // Create provider
    provider := openai.NewOpenAIProvider(
        "openai",
        "gpt-4o-mini",
        os.Getenv("OPENAI_API_KEY"),
        openai.DefaultProviderDefaults(),
        false,
    )
    defer provider.Close()

    // Build pipeline with tools
    pipe := pipeline.NewPipeline(
        middleware.ProviderMiddleware(provider, toolRegistry, &pipeline.ToolPolicy{
            ToolChoice: "auto",
            MaxRounds:  5,
        }, &middleware.ProviderMiddlewareConfig{
            MaxTokens:   1500,
            Temperature: 0.7,
        }),
    )
    defer pipe.Shutdown(context.Background())

    // Interactive loop
    fmt.Println("\nTool-enabled chatbot ready! Type 'exit' to quit.")
    fmt.Print("\nYou: ")

    scanner := bufio.NewScanner(os.Stdin)
    for scanner.Scan() {
        input := strings.TrimSpace(scanner.Text())

        if input == "exit" {
            break
        }

        if input == "" {
            fmt.Print("You: ")
            continue
        }

        result, err := pipe.Execute(ctx, "user", input)
        if err != nil {
            log.Printf("Error: %v\n", err)
            fmt.Print("You: ")
            continue
        }

        fmt.Printf("\nBot: %s\n\n", result.Response.Content)
        fmt.Print("You: ")
    }

    fmt.Println("Goodbye!")
}

Step 3: Test with Files

Create test directory and files:

mkdir -p /tmp/allowed
echo "Hello from file!" > /tmp/allowed/test.txt
echo "Shopping: milk, eggs, bread" > /tmp/allowed/shopping.txt

Run the bot:

go run main.go

Try these prompts:

You: Read the file /tmp/allowed/test.txt
Bot: The file contains: "Hello from file!"

You: List all files in /tmp/allowed
Bot: There are 2 files: test.txt and shopping.txt

You: What's in my shopping list?
Bot: Your shopping list contains: milk, eggs, and bread

You: Create a new file called notes.txt with "Meeting at 3pm"
Bot: I've created notes.txt with your message.

The LLM automatically uses tools to complete tasks! 🎉

Understanding Tool Calling

How Tools Work

1. Registration: Tools are registered with descriptions
2. LLM Decision: LLM decides when to use tools
3. Execution: Runtime executes tool calls
4. Response: LLM sees results and responds to user

Tool Policy

policy := &pipeline.ToolPolicy{
    ToolChoice: "auto",    // "auto", "required", "none"
    MaxRounds:  5,         // Max back-and-forth with tools
}

• auto: LLM chooses when to use tools
• required: LLM must use at least one tool
• none: Tools disabled

Available Filesystem Tools

• read_file: Read file contents
• write_file: Write to file
• list_directory: List directory contents
• create_directory: Create directory
• move_file: Move/rename file
• delete_file: Delete file

Add Memory Server

Install memory MCP server for persistent key-value storage:

// Register memory server
mcpRegistry.RegisterServer(mcp.ServerConfig{
    Name:    "memory",
    Command: "npx",
    Args:    []string{"-y", "@modelcontextprotocol/server-memory"},
})

Memory tools:

• store_memory: Save data by key
• retrieve_memory: Get data by key

Try:

You: Remember that my favorite color is blue
Bot: I've stored that information.

You: What's my favorite color?
Bot: Your favorite color is blue.

Complete Example with Multiple Servers

package main

import (
    "bufio"
    "context"
    "fmt"
    "log"
    "os"
    "strings"

    "github.com/AltairaLabs/PromptKit/runtime/mcp"
    "github.com/AltairaLabs/PromptKit/runtime/pipeline"
    "github.com/AltairaLabs/PromptKit/runtime/pipeline/middleware"
    "github.com/AltairaLabs/PromptKit/runtime/providers/openai"
    "github.com/AltairaLabs/PromptKit/runtime/statestore"
    "github.com/AltairaLabs/PromptKit/runtime/tools"
)

func main() {
    // MCP setup
    mcpRegistry := mcp.NewRegistry()
    defer mcpRegistry.Close()

    // Register servers
    servers := []mcp.ServerConfig{
        {
            Name:    "filesystem",
            Command: "npx",
            Args:    []string{"-y", "@modelcontextprotocol/server-filesystem", "/tmp/allowed"},
        },
        {
            Name:    "memory",
            Command: "npx",
            Args:    []string{"-y", "@modelcontextprotocol/server-memory"},
        },
    }

    for _, config := range servers {
        if err := mcpRegistry.RegisterServer(config); err != nil {
            log.Fatalf("Failed to register %s: %v", config.Name, err)
        }
        fmt.Printf("Registered MCP server: %s\n", config.Name)
    }

    // Tool registry setup
    toolRegistry := tools.NewRegistry()
    toolRegistry.RegisterExecutor(tools.NewMCPExecutor(mcpRegistry))

    // Discover tools
    ctx := context.Background()
    serverTools, _ := mcpRegistry.ListAllTools(ctx)
    for serverName, mcpTools := range serverTools {
        fmt.Printf("\n%s tools:\n", serverName)
        for _, tool := range mcpTools {
            toolRegistry.Register(&tools.ToolDescriptor{
                Name:        tool.Name,
                Description: tool.Description,
                InputSchema: tool.InputSchema,
                Mode:        "mcp",
            })
            fmt.Printf("  - %s: %s\n", tool.Name, tool.Description)
        }
    }

    // Provider and pipeline
    provider := openai.NewOpenAIProvider(
        "openai",
        "gpt-4o-mini",
        os.Getenv("OPENAI_API_KEY"),
        openai.DefaultProviderDefaults(),
        false,
    )
    defer provider.Close()

    store := statestore.NewInMemoryStateStore()

    pipe := pipeline.NewPipeline(
        middleware.StateMiddleware(store),
        middleware.ProviderMiddleware(provider, toolRegistry, &pipeline.ToolPolicy{
            ToolChoice: "auto",
            MaxRounds:  5,
        }, &middleware.ProviderMiddlewareConfig{
            MaxTokens:   1500,
            Temperature: 0.7,
        }),
    )
    defer pipe.Shutdown(ctx)

    sessionID := "tool-session"

    fmt.Println("\n=== Tool-Enabled Agent ===")
    fmt.Println("Available: filesystem and memory tools")
    fmt.Println("Type 'exit' to quit\n")

    scanner := bufio.NewScanner(os.Stdin)
    fmt.Print("You: ")

    for scanner.Scan() {
        input := strings.TrimSpace(scanner.Text())

        if input == "exit" {
            break
        }

        if input == "" {
            fmt.Print("You: ")
            continue
        }

        result, err := pipe.ExecuteWithContext(ctx, sessionID, "user", input)
        if err != nil {
            log.Printf("\nError: %v\n\n", err)
            fmt.Print("You: ")
            continue
        }

        fmt.Printf("\nAgent: %s\n\n", result.Response.Content)
        fmt.Printf("[Cost: $%.6f]\n\n", result.Cost.TotalCost)
        fmt.Print("You: ")
    }

    fmt.Println("Goodbye!")
}

Common Issues

MCP server won’t start

Problem: npx command fails.

Solution: Install Node.js or specify full path to npx.

Tools not working

Problem: LLM doesn’t use tools.

Solution: Use clear prompts: “Read the file test.txt” not “What’s in that file?”

Permission errors

Problem: Can’t access files.

Solution: Ensure path is within allowed directory: /tmp/allowed/file.txt

What You’ve Learned

✅ Set up MCP servers
✅ Register external tools
✅ Enable automatic tool calling
✅ Handle tool execution
✅ Build tool-enabled agents
✅ Use multiple MCP servers

Next Steps

Continue to Tutorial 4: Validation & Guardrails to add content safety.

See Also

• Integrate MCP - More MCP patterns
• Tools & MCP Reference - Complete API