Update website/src/pages/en/ai-suite/token-api-mcp/introduction.mdx

Co-authored-by: Benoît Rouleau <[email protected]>

Author: 0237h

website/src/pages/en/ai-suite/token-api-mcp/introduction.mdx

@@ -11,7 +11,7 @@ There are two types of MCP available for use:
 - A REST-based MCP, the default, that communicates with the Token API.
 - A SQL-based MCP, for advanced users, that allows for communicating with the backend databases that power the Token API.
 
-The REST-based MCP simply exposes the API endpoints to your LLM based on the OpenAPI specification (available at https://token-api.thegraph.com/openapi). It is the *recommended way* to setup an LLM with Token API as the set of tools it offers is straightforward to use for any language model. Additionnaly, it automatically stays up-to-date with new Token API releases so you don't miss any new features !
+The REST-based MCP simply exposes the API endpoints to your LLM based on the OpenAPI specification (available at https://token-api.thegraph.com/openapi). It is the *recommended way* to set up an LLM with Token API as the set of tools it offers is straightforward to use for any language model. Additionnaly, it automatically stays up-to-date with new Token API releases so you don't miss any new features!
 
 The SQL-based MCP provides the LLM tools to list databases and tables as well as run SQL queries directly on the data. It is meant for advanced users who need different use cases that the standard API endpoints cannot replicate. For best results, it is advised to use an LLM model specifically tuned for working with SQL as general purpose LLMs models (like Sonnet, Gemini, etc.) might not be able to generate valid queries efficiently.