1. Giving the model too many choices. If you have a lot of options (like a bunch of MCP servers) what you often see in practice is that it's like a dice roll which option is chosen, even if the best choice is pretty obvious to a human. This is even tough when you just have a single branch in the prompt where the model has to choose path A or B. It's hard to get it to choose intelligently vs. randomly.
2. Global scope. The prompts related to each MCP all get mixed together in the system prompt, along with the prompting for the tool that's integrating them. They can easily be modifying each other's behavior in unpredictable ways.
1. Giving the model too many choices. If you have a lot of options (like a bunch of MCP servers) what you often see in practice is that it's like a dice roll which option is chosen, even if the best choice is pretty obvious to a human. This is even tough when you just have a single branch in the prompt where the model has to choose path A or B. It's hard to get it to choose intelligently vs. randomly.
2. Global scope. The prompts related to each MCP all get mixed together in the system prompt, along with the prompting for the tool that's integrating them. They can easily be modifying each other's behavior in unpredictable ways.