MCP Tools

Enhance your AI agents with powerful external tools and services using the Model Context Protocol (MCP). Connect to file systems, APIs, databases, and more to extend your agent’s capabilities beyond text-based responses.
MCP Tools Dashboard

What are MCP Tools?

The Model Context Protocol (MCP) is a standardized way to connect AI agents to external tools and services. MCP tools enable your AI agents to:

File Operations

Read, write, and manage files and directories

API Integration

Connect to external APIs and web services

Database Access

Query and interact with databases

Git Operations

Manage version control repositories

Web Search

Search the internet for real-time information

Weather Data

Access weather and environmental data

Transport Types

MCP tools support three different transport protocols for communication:

Managing MCP Tools

Adding MCP Tools

ChatterMate provides two ways to add MCP tools to your agents:

Create Tool

Configure new MCP servers from scratch or use presets

Link Existing

Connect to MCP tools already configured in your organization

Tool Sharing

MCP tools can be shared across multiple agents within your organization:
  • Organization-wide: Tools created by any team member are available to all agents
  • Reusable Configuration: Set up once, use across multiple agents
  • Centralized Management: Update tool configuration in one place
  • Access Control: Only organization members can access shared tools

Use Cases for Tool Sharing

  • Common API integrations across support and sales agents
  • Shared file system access for documentation
  • Organization-wide weather or search capabilities
  • Centralized database connections
When you update a shared MCP tool configuration, all agents using that tool will automatically use the updated settings.
ChatterMate includes pre-configured templates for common use cases:

File System Access

{
  "name": "File System",
  "description": "Access and manage files and directories",
  "transport_type": "stdio",
  "command": "uvx",
  "args": ["@modelcontextprotocol/server-filesystem"],
  "env_vars": {
    "ALLOWED_DIRECTORIES": "/path/to/allowed/directory"
  }
}

Git Repository Management

{
  "name": "Git Repository",
  "description": "Interact with Git repositories",
  "transport_type": "stdio",
  "command": "uvx",
  "args": ["@modelcontextprotocol/server-git"],
  "env_vars": {}
}

Web Search Integration

{
  "name": "Web Search",
  "description": "Search the web using Brave Search API",
  "transport_type": "stdio",
  "command": "uvx",
  "args": ["@modelcontextprotocol/server-brave-search"],
  "env_vars": {
    "BRAVE_API_KEY": "your-api-key"
  }
}

Weather Information

{
  "name": "Weather",
  "description": "Get weather information",
  "transport_type": "stdio",
  "command": "uvx",
  "args": ["@modelcontextprotocol/server-weather"],
  "env_vars": {
    "WEATHER_API_KEY": "your-api-key"
  }
}

Configuration Guide

STDIO Transport Configuration

For command-line tools and local services:

Required Fields

  • Command: The executable command (e.g., npx, uvx, node)
  • Args: Array of command arguments

Optional Fields

  • Environment Variables: Key-value pairs for environment configuration
  • Working Directory: Set the working directory for the process

Example Configuration

{
  "command": "npx",
  "args": ["-y", "@modelcontextprotocol/server-filesystem"],
  "env_vars": {
    "ALLOWED_DIRECTORIES": "/home/user/documents,/home/user/projects",
    "READONLY": "false"
  }
}

SSE Transport Configuration

For server-sent events and streaming data:

Required Fields

  • URL: The SSE endpoint URL

Optional Fields

  • Headers: HTTP headers for authentication or configuration
  • SSE Read Timeout: Maximum time to wait for events (default: 60 seconds)
  • Timeout: Connection timeout (default: 30 seconds)

Example Configuration

{
  "url": "https://api.example.com/sse/events",
  "headers": {
    "Authorization": "Bearer your-token",
    "Accept": "text/event-stream"
  },
  "sse_read_timeout": 120,
  "timeout": 45
}

HTTP Transport Configuration

For REST APIs and web services:

Required Fields

  • URL: The API base URL

Optional Fields

  • Headers: HTTP headers for authentication or content type
  • Timeout: Request timeout (default: 30 seconds)
  • Terminate on Close: Whether to terminate the connection when the chat session ends

Example Configuration

{
  "url": "https://api.example.com",
  "headers": {
    "Authorization": "Bearer your-api-key",
    "Content-Type": "application/json"
  },
  "timeout": 60,
  "terminate_on_close": true
}

Security Considerations

Environment Variables

  • Store sensitive data like API keys in environment variables
  • Never hardcode credentials in configuration
  • Use secure key management practices

Access Control

  • Limit file system access to specific directories
  • Use read-only permissions when possible
  • Validate API endpoints and permissions

Network Security

  • Use HTTPS for all external connections
  • Validate SSL certificates
  • Configure appropriate timeouts
MCP tools run with the same permissions as your application. Always validate tool configurations and limit access to sensitive resources.

Tool Status Management

Tool States

Troubleshooting

Common issues and solutions:
  1. Connection Timeouts
    • Increase timeout values in configuration
    • Check network connectivity
    • Verify service availability
  2. Authentication Errors
    • Validate API keys and credentials
    • Check header configuration
    • Ensure proper permissions
  3. Command Not Found (STDIO)
    • Verify command is installed and in PATH
    • Check argument syntax
    • Test command manually

Best Practices

Tool Configuration

  1. Use Environment Variables for sensitive data
  2. Test Locally before deploying to agents
  3. Set Appropriate Timeouts to prevent hanging
  4. Document Tool Purpose in descriptions
  5. Use Descriptive Names for easy identification

Performance Optimization

  1. Enable Only Needed Tools to reduce startup time
  2. Configure Reasonable Timeouts to prevent delays
  3. Monitor Tool Usage and performance
  4. Cache Results when possible

Security Guidelines

  1. Principle of Least Privilege - grant minimal necessary access
  2. Regular Credential Rotation for API keys
  3. Audit Tool Access and usage patterns
  4. Secure Configuration Storage for sensitive settings

Monitoring and Debugging

Tool Logs

  • Access tool execution logs through the dashboard
  • Monitor connection status and errors
  • Track tool usage and performance metrics

Debug Mode

  • Enable verbose logging for troubleshooting
  • Test tool connections independently
  • Validate configuration parameters

Performance Metrics

  • Track tool response times
  • Monitor success/failure rates
  • Analyze usage patterns

Limitations

  • Maximum 10 MCP tools per agent
  • STDIO tools require server-side command availability
  • Network-based tools depend on external service reliability
  • Some tools may require specific software dependencies
  • Tool execution timeout maximum: 300 seconds

Integration Examples

Customer Support with File Access

{
  "name": "Support Documents",
  "description": "Access customer support documentation",
  "transport_type": "stdio",
  "command": "uvx",
  "args": ["@modelcontextprotocol/server-filesystem"],
  "env_vars": {
    "ALLOWED_DIRECTORIES": "/var/www/support-docs",
    "READONLY": "true"
  }
}

Sales Agent with CRM Integration

{
  "name": "CRM API",
  "description": "Customer relationship management integration",
  "transport_type": "http",
  "url": "https://api.salesforce.com",
  "headers": {
    "Authorization": "Bearer sf_token",
    "Content-Type": "application/json"
  }
}

Technical Support with Git Access

{
  "name": "Code Repository",
  "description": "Access to technical documentation repository",
  "transport_type": "stdio",
  "command": "uvx",
  "args": ["@modelcontextprotocol/server-git"],
  "env_vars": {
    "GIT_REPO_PATH": "/opt/repositories/tech-docs"
  }
}

What’s Next?

After configuring MCP tools:
  1. Test tool functionality with your agent
  2. Monitor tool performance and usage
  3. Configure additional tools as needed
  4. Review security and access permissions

Agent Testing

Next: Learn how to test your agent with MCP tools

AI Customization

Back: Configure your AI agent settings