Common MCP Errors

Solutions to common MCP server connection and configuration issues

This guide covers common errors you might encounter when working with MCP servers and how to resolve them.

Connection Issues

Server fails to start or connect

• Use absolute paths: Specify the full path to your server

  • ✅ Good: /Users/yourname/project/server.py
  • ❌ Bad: ./server.py or server.py

• For uv projects: Use the --directory flag with absolute path

  uv run --directory /Users/username/weather-mcp mcp.py
  

• Test your command first: Run the server command manually in a terminal to verify it works before adding it to Inspector

• For HTTP servers: Verify the URL is accessible

  • Test with curl or a browser first

Authentication Issues

Server fails to connect with authentication errors

If your server is failing to connect, first verify you’ve selected the correct authentication option:

• No Authentication - Use this for local or development servers that don’t require authentication
• Bearer Token - Use this if you already have an API token from the server
• OAuth 2.0 - Use this for servers that require OAuth authorization flow

Getting 401 Unauthorized errors

If you’re seeing 401 Unauthorized errors when trying to connect to your server, this typically means the server requires authentication that hasn’t been set up yet.

Solution:

1. Change your authentication type to OAuth 2.0 in the server configuration
2. Go through the OAuth authorization flow to obtain credentials
3. Use the OAuth Debugger to troubleshoot any issues with the OAuth process

The OAuth Debugger helps you step through each part of the authorization process and identify where things might be going wrong.

Common Configuration Mistakes

• Missing required environment variables
• Incorrect transport type selection
• Typos in server URLs or commands
• Missing file permissions or executable flags

Chat Model Limit

”MCPJam model limit reached” warning

MCPJam provides free frontier models for chat. When you hit the daily usage limit, the chat surface shows a warning:

MCPJam model limit reached. Add your own API key under LLM Providers in Settings to continue now, or try again in N minutes.

This is an expected quota state, not an error with your MCP server.

To continue immediately:

1. Go to Settings → LLM Providers
2. Add an API key for any supported provider (OpenAI, Anthropic, Gemini, etc.)
3. Select that provider’s model in the chat model picker

To wait for the limit to reset: The warning includes the retry window. Free quota resets daily.

Getting Help

If you’re still experiencing issues:

1. Check server documentation

   • Review the MCP server’s specific documentation
   • Look for known issues or troubleshooting guides

2. Community support

   • Join our Discord for community help
   • Check GitHub Issues for similar problems