I see many of you asking about the differences between using this versus web_fetch. The main differences are the quality of the data and token usage.
1. Standard web_fetch tools usually dump raw HTML into the context (including navbars, scripts, and footer noise). This wastes a huge amount of tokens and distracts the model. toMCP runs the page through a readability parser and converts it to clean markdown before sending it to the AI.
2. Adding a website as an MCP Resource pins it as a permanent, read-only context, making it ideal for keeping documentation constantly available. This differs from the web_fetch tool, which is an on-demand action the AI only triggers when it decides to, meaning the data isn't permanently attached to your project.
1. Standard web_fetch tools usually dump raw HTML into the context (including navbars, scripts, and footer noise). This wastes a huge amount of tokens and distracts the model. toMCP runs the page through a readability parser and converts it to clean markdown before sending it to the AI.
2. Adding a website as an MCP Resource pins it as a permanent, read-only context, making it ideal for keeping documentation constantly available. This differs from the web_fetch tool, which is an on-demand action the AI only triggers when it decides to, meaning the data isn't permanently attached to your project.