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MCP Tools Overview

What is MCP?​

Model Context Protocol (MCP) is a framework that enables AI models to interact with external tools and services. In Codebolt, MCP tools extend the AI's capabilities beyond text generation to include real-world actions and integrations.

Core Concepts​

Tools​

  • External Integrations: Connect AI to databases, APIs, and services
  • Action Capabilities: Perform operations beyond code generation
  • Real-time Data: Access live information and current system states
  • Bidirectional Communication: Tools can send data back to the AI

Resources​

  • File Access: Read and modify files in your project
  • Database Connections: Query and update database records
  • API Endpoints: Interact with web services and REST APIs
  • System Information: Access system metrics and configurations

Prompts​

  • Dynamic Context: Generate contextual prompts based on current state
  • Tool-Specific: Specialized prompts for different tool types
  • User Preferences: Customize prompts based on your workflow
  • Adaptive Responses: Prompts that evolve with your project

Available MCP Tools​

Development Tools​

  • Git Integration: Commit, push, pull, and manage repositories
  • Package Managers: Install and manage dependencies (npm, pip, etc.)
  • Build Systems: Execute build scripts and deployment processes
  • Testing Frameworks: Run tests and generate coverage reports

Database Tools​

  • SQL Databases: MySQL, PostgreSQL, SQLite connections
  • NoSQL Databases: MongoDB, Redis integrations
  • Query Builder: Visual query construction and execution
  • Schema Management: Database migration and schema updates

API Integration Tools​

  • REST Clients: HTTP requests with authentication
  • GraphQL: Query and mutation operations
  • Webhook Management: Set up and manage webhook endpoints
  • API Documentation: Generate and maintain API docs

File System Tools​

  • File Operations: Advanced file manipulation beyond basic editor functions
  • Archive Management: Create and extract ZIP, TAR files
  • File Synchronization: Sync files between different locations
  • Permission Management: Handle file and folder permissions

Cloud Services​

  • AWS Integration: EC2, S3, Lambda, and other AWS services
  • Google Cloud: GCP service integrations
  • Azure Services: Microsoft Azure tool connections
  • Container Management: Docker and Kubernetes operations

Monitoring & Analytics​

  • Log Analysis: Parse and analyze application logs
  • Performance Metrics: System and application performance data
  • Error Tracking: Integration with error monitoring services
  • Usage Analytics: Track application usage patterns

Benefits of MCP Tools​

Enhanced AI Capabilities​

  • Beyond Code: AI can perform actual operations, not just suggest code
  • Context Awareness: Tools provide real-time context about your environment
  • Automated Workflows: Chain tools together for complex operations
  • Reduced Manual Work: AI handles routine tasks automatically

Improved Development Experience​

  • Unified Interface: Access all tools through the chat interface
  • Natural Language: Control tools using natural language commands
  • Smart Suggestions: AI suggests relevant tools based on context
  • Error Handling: Intelligent error recovery and suggestions

Extensibility​

  • Custom Tools: Create your own MCP tools for specific needs
  • Plugin Architecture: Easily add new capabilities
  • Team Sharing: Share custom tools with your development team
  • Marketplace: Access community-developed tools

Getting Started​

Prerequisites​

  • Codebolt Editor installed and configured
  • Active AI model subscription
  • Necessary API keys for external services
  • Basic understanding of your development environment

Quick Setup​

  1. Enable MCP Tools: Activate MCP in your Codebolt settings
  2. Configure Credentials: Add API keys and connection strings
  3. Test Connection: Verify tools are working correctly
  4. Explore Examples: Try built-in tool examples

Best Practices​

  • Security First: Never share API keys or sensitive credentials
  • Start Simple: Begin with basic tools before moving to complex integrations
  • Test Thoroughly: Always test tools in development before production use
  • Monitor Usage: Keep track of tool usage and costs

Next Steps​

Common Use Cases​

Database Operations​

"Show me all users created in the last 7 days"
"Update the user profile table with new columns"
"Generate a report of database performance metrics"

API Management​

"Test the authentication endpoint with different user roles"
"Update the product catalog via the REST API"
"Generate client SDKs from the OpenAPI specification"

DevOps Automation​

"Deploy the latest version to staging environment"
"Check the status of all running containers"
"Set up a new CI/CD pipeline for this repository"

File Management​

"Sync all configuration files with the remote repository"
"Create a backup of the current project state"
"Generate documentation from code comments"