MCP Integration

Dispersl integrates seamlessly with various development tools and AI assistants through the Model Context Protocol (MCP), enabling your AI coding assistants to connect with Dispersl's multi-agent capabilities.

Quick Start

1. Get Your Dispersl MCP Key

First, obtain your Dispersl MCP key from your dashboard:

# Get your MCP key via API
curl -X GET "https://api.dispersl.com/v1/mcp/key" \
  -H "Authorization: Bearer YOUR_API_KEY"

2. Install Dispersl MCP Package

npm install dispersl-mcp

3. Configure Your AI Tool

Each AI tool has its own configuration method. Here's a basic example for Cursor:

{
  "mcpServers": {
    "dispersl": {
      "url": "https://dispersl.com/mcp/YOUR_DISPERSL_MCP_KEY"
    }
  }
}

4. Start Using Dispersl Agents

Once configured, you can use Dispersl's agents through your AI tool:

Ask your AI assistant:
"Use Dispersl to create a REST API with authentication and tests"

The AI will coordinate with Dispersl's multi-agent team to:
1. Plan the implementation
2. Generate the code
3. Create comprehensive tests
4. Set up version control
5. Generate documentation

Available MCP Tools

When connected to Dispersl via MCP, your AI assistant gains access to:

Multi-Agent Coordination

Plan tasks across multiple specialized agents
Coordinate workflows between coding, testing, and documentation agents
Monitor progress of complex development tasks

Code Generation

Generate APIs with proper structure and error handling
Create database models and migrations
Implement business logic with best practices
Optimize performance and security

Testing

Generate unit tests with high coverage
Create integration tests for APIs and services
Set up test automation and CI/CD pipelines
Generate test data and mocks

Version Control

Manage Git workflows with proper branching strategies
Handle merge conflicts automatically
Create releases and tags
Set up CI/CD configurations

Documentation

Generate API documentation from code
Create README files and setup guides
Write code comments and inline documentation
Maintain changelogs and release notes

Security and Best Practices

MCP Key Security

Keep your MCP key secure: Never share it or commit it to version control
Use environment variables: Store keys in secure environment variables
Rotate regularly: Generate new keys periodically for security
Monitor usage: Track MCP key usage through analytics

Configuration Best Practices

Project-specific configs: Use project-specific MCP configurations when possible
Global fallbacks: Set up global configurations for commonly used tools
Version control: Don't commit MCP configurations with keys to version control
Team sharing: Use team-specific keys for collaborative projects

Usage Optimization

Clear prompts: Provide specific, detailed prompts for better agent coordination
Context sharing: Include relevant project context in your requests
Monitor performance: Track agent performance and adjust configurations
Resource management: Be mindful of token usage and API limits

Troubleshooting

Common Issues

Connection Failed

Verify your MCP key is correct and active
Check network connectivity and firewall settings
Ensure the MCP server URL is properly formatted

Agent Not Responding

Check if you have sufficient API credits
Verify the agent type is available in your plan
Review rate limits and usage quotas

Configuration Errors

Validate JSON syntax in configuration files
Ensure file paths and permissions are correct
Check for conflicting MCP server configurations

Getting Help

Documentation: Check the specific integration guide for your tool
Community: Join our Discord for community support
Support: Contact support for enterprise assistance
Status: Check our status page for service updates

Advanced Features

Custom Workflows

Create custom MCP workflows that combine multiple Dispersl agents:

{
  "workflow": "full-stack-development",
  "agents": ["plan", "code", "test", "git", "docs"],
  "coordination": "sequential",
  "error_handling": "retry_with_fallback"
}

Integration Monitoring

Monitor your MCP integrations through the analytics dashboard:

Connection status and uptime
Agent usage patterns and performance
Token consumption and costs
Error rates and resolution times

Team Collaboration

Set up team-wide MCP configurations:

Shared agent configurations
Team-specific workflows
Collaborative development patterns
Centralized monitoring and reporting

Next Steps

Choose your AI tool from the supported applications
Follow the specific integration guide for detailed setup instructions
Start with simple tasks to test the integration
Scale up to complex workflows as you become comfortable
Monitor and optimize your usage patterns

Ready to get started? Choose your preferred AI development tool from the list above and follow the detailed integration guide.

Mcp Copilot