AgentQL + AgentAI: Complete MCP Integration
AgentQL is a MCP server that Enable AI agents to get structured data from unstructured web with AgentQL..
When integrated with AgentAI, you can:
- Extract structured data from web pages using natural language
- Scrape web data with structured field definitions
- Monitor web pages for content changes
This guide provides step-by-step instructions to set up AgentQL in AgentAI, including configuration, examples, and troubleshooting.
What You'll Achieve
After completing this setup:
- AgentQL will be fully integrated and operational
- You can use AgentQL tools directly in AgentAI
- All AgentQL capabilities will be available for your workflows
- Access to 3 different tools
Prerequisites
Before starting, ensure you have:
- API key from AgentQL Dev Portal
- AgentAI installed and configured
- Compatible operating system (Windows, macOS, Linux)
Installation
Step 1: Install AgentQL
Configuration
Step 2: Configure AgentAI
- Open AgentAI settings
- Navigate to MCP server configuration
- Add AgentQL server with appropriate settings
- Save and restart if needed
Examples
Once configured, you can use AgentQL in AgentAI:
E-commerce Product Monitoring
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Ask AgentAI: "Extract product details from Amazon search results"
Expected Result: undefined
News Article Analysis
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Ask AgentAI: "Get headlines, summaries, and publish dates from news site"
Expected Result: undefined
Social Media Insights
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Ask AgentAI: "Extract post engagement from social media feeds"
Expected Result: undefined
Testing Your Setup
- Launch AgentAI
- Verify AgentQL is available in the tools list
- Test basic AgentQL functionality
Troubleshooting
Common Issues
Compilation Errors
Symptoms: Cargo build fails, Missing dependencies errors
Cause: Missing Rust toolchain or system dependencies
Solution:
- Ensure latest Rust toolchain is installed
- Install platform-specific build tools
- Check Cargo.toml for correct dependency versions
- Run cargo update to refresh dependencies
MCP Server Not Found
Symptoms: Runtime error finding server, Server command not found
Cause: MCP server not installed or not in PATH
Solution:
- Verify MCP server installation
- Use absolute path to server binary
- Ensure server has execute permissions
- Check environment variables are set correctly
Agent Initialization Fails
Symptoms: Agent creation errors, API key issues
Cause: Missing API keys or invalid configuration
Solution:
- Set required environment variables for AI provider
- Verify API key validity and permissions
- Check network connectivity to AI service
- Review AgentAI documentation for latest changes
AgentQL not appearing in AgentAI
Symptoms: Server not listed, Tools not available
Cause: Configuration or installation issue
Solution:
- Verify configuration syntax
- Check AgentQL installation
- Restart AgentAI
- Check logs for error messages
Next Steps
Now that AgentQL is integrated with AgentAI:
- Explore all AgentQL capabilities through AgentAI
- Check out other MCP servers that work with AgentAI
- Join the MCP community for tips and support
- Consider contributing to AgentQL development
Need Help?
- Search for AgentQL documentation
- Check the AgentAI MCP guide
- Join the MCP community discussions