Voice and Text Conversations

The Conversation screen is your primary interface for interacting with AI through voice and text. It provides seamless access to your configured MCP tools while maintaining conversation context and history.

Overview

The Conversation screen combines powerful voice recognition with text input capabilities, allowing you to control MCP servers naturally. Whether you're checking pull requests, monitoring errors, or browsing community discussions, the conversation interface adapts to your preferred interaction style.

Key Features

• Dual Input Methods: Switch seamlessly between voice and text input
• Real-time Transcription: See your voice commands transcribed instantly
• Tool Integration: Access all your enabled MCP tools within conversations
• Context Retention: Maintains conversation context for follow-up questions
• Auto-save: All conversations are automatically saved for future reference

Voice Interaction

Getting Started with Voice

1. Tap the microphone button to begin voice input
2. Speak naturally - the AI understands developer terminology and commands
3. Release to send or tap again to cancel
4. View transcription in real-time as you speak

Voice Command Examples

"Check the status of pull request 123 in my main repository"
"Show me critical errors from the last hour in production"
"What's trending in the machine learning subreddit today?"
"Run the customer onboarding scenario in Make"

Voice Recognition Tips

• Speak clearly but naturally - no need to over-enunciate
• Use specific terms - the AI is trained on developer vocabulary
• Include context - mention project names, issue numbers, or timeframes
• Pause briefly between complex commands for better recognition

Text Input

Using Text Commands

1. Tap the text field at the bottom of the screen
2. Type your command or question
3. Press send to submit your message
4. Edit before sending if needed

Text Input Advantages

• Complex queries: Ideal for detailed technical questions
• Code snippets: Include code or configuration in your messages
• Quiet environments: Use when voice isn't appropriate
• Precision: Perfect for specific issue numbers or exact terms

Tool Usage in Conversations

Accessing MCP Tools

Your conversation can leverage any of your enabled MCP tools:

1. Automatic detection: The AI identifies which tools to use based on your request
2. Multi-tool operations: Combine multiple tools in a single conversation
3. Tool responses: See structured data from tool executions
4. Follow-up actions: Continue working with tool results

Tool Command Patterns

GitHub: "Create an issue titled 'Bug in auth flow' in the backend repo"
Sentry: "Assign error ID 789 to the frontend team"
Reddit: "Search r/programming for posts about Rust performance"
Make: "Trigger the data sync scenario with today's date"

Conversation Management

During Conversations

• View AI responses with syntax highlighting for code
• See tool executions with clear status indicators
• Copy responses for use in other applications
• Share conversations with team members

Conversation Controls

• New Conversation: Start fresh with cleared context
• Clear History: Remove all messages from current conversation
• Export: Save conversation as text or markdown
• Settings Access: Quick access to conversation preferences

Best Practices

Effective Communication

1. Be specific: Include relevant details like project names, issue numbers
2. Use context: Reference previous messages with "that" or "the above"
3. Chain commands: Build complex workflows through conversation
4. Verify actions: Ask for confirmation before critical operations

Common Workflows

Development Review

"Show me all open pull requests assigned to me"
"What changes were made in PR 456?"
"Are there any failing tests in that PR?"
"Approve and merge it to main"

Error Investigation

"Check for new errors in the payment service"
"Show me the stack trace for error 12345"
"How many users are affected?"
"Create a GitHub issue for this error"

Community Monitoring

"What's new in r/webdev today?"
"Filter for posts about React performance"
"Show me the top comment on that post"
"Save this for our team discussion"

Troubleshooting

Voice Recognition Issues

• Background noise: Move to a quieter location
• Network connectivity: Ensure stable internet connection
• Microphone permissions: Check app permissions in settings
• Language settings: Verify language matches your speech

Response Issues

• Tool availability: Ensure required MCP servers are connected
• Rate limits: Some tools may have usage restrictions
• Context confusion: Start a new conversation if context is mixed
• Connection status: Check MCP server connections

Start a conversation now and experience the power of voice-controlled MCP server management!