AI Tasks + fast-agent: Complete MCP Integration
AI Tasks is a MCP server that Let the AI manage complex plans with integrated task management and tracking tools. Supports STDIO, SSE and Streamable HTTP transports..
When integrated with fast-agent, you can:
- Create a new project plan with tasks
- Add a task to an existing plan
- Update task completion status
This guide provides step-by-step instructions to set up AI Tasks in fast-agent, including configuration, examples, and troubleshooting.
What You'll Achieve
After completing this setup:
- AI Tasks will be fully integrated and operational
- You can use AI Tasks tools directly in fast-agent
- All AI Tasks capabilities will be available for your workflows
- Access to 4 different tools
Prerequisites
Before starting, ensure you have:
- fast-agent installed and configured
- Compatible operating system (Node.js, Cross-platform, Edge Environments)
Installation
Step 1: Install AI Tasks
Configuration
Step 2: Configure fast-agent
- Open fast-agent settings
- Navigate to MCP server configuration
- Add AI Tasks server with appropriate settings
- Save and restart if needed
Examples
Once configured, you can use AI Tasks in fast-agent:
Project Management
undefined
Ask fast-agent: "Create a plan for mobile app development with tasks"
Expected Result: undefined
Task Tracking
undefined
Ask fast-agent: "Show all in-progress tasks and assign priorities"
Expected Result: undefined
Sprint Planning
undefined
Ask fast-agent: "Create 2-week sprint with 20 story points"
Expected Result: undefined
Testing Your Setup
- Launch fast-agent
- Verify AI Tasks is available in the tools list
- Test basic AI Tasks functionality
Troubleshooting
Common Issues
Poor Performance
Symptoms: Slow startup, High memory usage, Slow tool execution
Cause: Suboptimal configuration or resource constraints
Solution:
- Tune concurrency and pool size settings
- Optimize MCP server performance
- Check system resources and limits
- Profile application for bottlenecks
Agent Crashes Under Load
Symptoms: Out of memory errors, Process crashes
Cause: Resource limits exceeded
Solution:
- Reduce concurrency limits
- Increase memory limits if possible
- Implement graceful degradation
- Monitor resource usage patterns
MCP Server Timeouts
Symptoms: Tool execution timeouts, Connection errors
Cause: Server overload or network issues
Solution:
- Increase timeout values
- Implement retry logic
- Scale MCP server infrastructure
- Use connection pooling and caching
AI Tasks not appearing in fast-agent
Symptoms: Server not listed, Tools not available
Cause: Configuration or installation issue
Solution:
- Verify configuration syntax
- Check AI Tasks installation
- Restart fast-agent
- Check logs for error messages
Next Steps
Now that AI Tasks is integrated with fast-agent:
- Explore all AI Tasks capabilities through fast-agent
- Check out other MCP servers that work with fast-agent
- Join the MCP community for tips and support
- Consider contributing to AI Tasks development
Need Help?
- Search for AI Tasks documentation
- Check the fast-agent MCP guide
- Join the MCP community discussions