beginner⏱️ 16-26 minutes📅 Updated June 2026

Step-by-step guide to integrate AI Tasks MCP server with mcp-use. Includes create_plan and add_task.

AI Tasks + mcp-use: 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 mcp-use, 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 mcp-use, 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 mcp-use
  • All AI Tasks capabilities will be available for your workflows
  • Access to 4 different tools

Prerequisites

Before starting, ensure you have:

  • mcp-use installed and configured
  • Compatible operating system (Python 3.8+, Node.js 16+, pip Installation, npm/yarn Installation)

Installation

Step 1: Install AI Tasks

Configuration

Step 2: Configure mcp-use

  1. Open mcp-use settings
  2. Navigate to MCP server configuration
  3. Add AI Tasks server with appropriate settings
  4. Save and restart if needed

Examples

Once configured, you can use AI Tasks in mcp-use:

Project Management

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Ask mcp-use: "Create a plan for mobile app development with tasks"

Expected Result: undefined

Task Tracking

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Ask mcp-use: "Show all in-progress tasks and assign priorities"

Expected Result: undefined

Sprint Planning

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Ask mcp-use: "Create 2-week sprint with 20 story points"

Expected Result: undefined

Testing Your Setup

  1. Launch mcp-use
  2. Verify AI Tasks is available in the tools list
  3. Test basic AI Tasks functionality

Troubleshooting

Common Issues

Connection Refused or Server Unreachable

Symptoms: ECONNREFUSED error, Connection timeout, Cannot reach server

Cause: MCP server not running or incorrect URL

Solution:

  • Verify MCP server is running and accessible
  • Check server URL is correct (protocol, host, port, path)
  • Test server URL in browser or with curl to confirm it responds
  • Ensure firewall allows connections to server port
  • Verify CORS settings if accessing from browser

Import Errors or Module Not Found

Symptoms: ModuleNotFoundError: mcp_use, Cannot find module "mcp-use"

Cause: Package not installed or wrong environment

Solution:

  • Verify installation: pip show mcp-use (Python) or npm list mcp-use (JS)
  • Ensure using correct Python virtual environment or Node.js project
  • Reinstall package: pip install --upgrade mcp-use or npm install mcp-use
  • Check package.json or requirements.txt includes mcp-use

Tool Discovery Returns Empty List

Symptoms: list_tools() returns [], No tools available, Tools not found

Cause: MCP server not properly configured or not exposing tools

Solution:

  • Verify MCP server is properly initialized and configured
  • Check server logs to confirm tools are registered
  • Test server directly with MCP inspector or test client
  • Ensure server implements MCP protocol correctly
  • Verify transport type (HTTP/SSE) matches server configuration

Tool Execution Fails or Returns Errors

Symptoms: Tool call throws exception, Invalid arguments error, Execution timeout

Cause: Incorrect arguments or server-side execution failure

Solution:

  • Verify tool arguments match schema definition from list_tools()
  • Check required arguments are provided with correct types
  • Review server logs for detailed error messages
  • Test tool with minimal valid arguments first
  • Increase timeout if tool requires longer execution time

LangChain.js Integration Not Working

Symptoms: getLangChainTools() fails, Tools not recognized by agent, Type errors

Cause: Version mismatch or incorrect integration setup

Solution:

  • Ensure LangChain.js version is compatible with mcp-use
  • Verify TypeScript version meets requirements
  • Check tool schema conversion is working correctly
  • Use latest versions of both mcp-use and LangChain.js
  • Review LangChain.js documentation for agent setup

Transport Type Errors (HTTP vs SSE)

Symptoms: SSE connection fails, HTTP polling not working, Event stream errors

Cause: Mismatch between client transport and server capabilities

Solution:

  • Verify server supports the transport type you are using
  • Try alternative transport: switch between "http" and "sse"
  • Check server documentation for supported transport types
  • For SSE, ensure server sends proper Content-Type: text/event-stream
  • For HTTP, verify server accepts POST requests with JSON payload

AI Tasks not appearing in mcp-use

Symptoms: Server not listed, Tools not available

Cause: Configuration or installation issue

Solution:

  • Verify configuration syntax
  • Check AI Tasks installation
  • Restart mcp-use
  • Check logs for error messages

Next Steps

Now that AI Tasks is integrated with mcp-use:

  • Explore all AI Tasks capabilities through mcp-use
  • Check out other MCP servers that work with mcp-use
  • Join the MCP community for tips and support
  • Consider contributing to AI Tasks development

Need Help?

Related Resources

More Integrations

Explore other MCP servers that work with mcp-use

Need Help?

Join the MCP community for support and discussions

AI Tasks + mcp-use: MCP Setup Guide (2026)