Document get_page MCP tool

ai/model-context-protocol.mdx

@@ -10,20 +10,29 @@ import { PreviewButton } from "/snippets/previewbutton.jsx"
 
 The Model Context Protocol (MCP) is an open protocol that creates standardized connections between AI applications and external services, like documentation. Mintlify generates an MCP server from your documentation, preparing your content for the broader AI ecosystem where any MCP client like Claude, Cursor, Goose, ChatGPT, and others can connect to your documentation.
 
-Your MCP server exposes a search tool for AI applications to query your documentation. Your users must connect your MCP server to their tools.
+Your MCP server exposes tools for AI applications to search your documentation and retrieve full page content. Your users must connect your MCP server to their tools.
 
 ### How MCP servers work
 
-When an AI application connects to your documentation MCP server, it can search your documentation directly in response to a user's prompt instead of relying on information from its training data or making a generic web search. Your MCP server provides access to all indexed content on your documentation site.
+When an AI application connects to your documentation MCP server, it can search your documentation and retrieve full page content directly in response to a user's prompt instead of relying on information from its training data or making a generic web search. Your MCP server provides access to all indexed content on your documentation site.
 
 - AI applications can proactively search your documentation while generating a response even if not explicitly asked to search your documentation for an answer.
-- AI applications determine when to use the search tool based on the context of the conversation and the relevance of your documentation.
-- Each search, also known as a tool call, happens during the generation process, so the AI application searches up-to-date information from your documentation to generate its response.
+- AI applications determine when to use the available tools based on the context of the conversation and the relevance of your documentation.
+- Each tool call happens during the generation process, so the AI application uses up-to-date information from your documentation to generate its response.
 
 <Tip>
   Some AI tools like Claude support both MCP and Skills. MCP gives the AI access to your documentation content, while Skills instruct the AI how to use that content effectively. They're complementary. MCP provides the data and Skills provide the instructions.
 </Tip>
 
+### MCP tools
+
+Your MCP server provides two tools that AI applications can use:
+
+- **Search**: Searches across your documentation to find relevant content, returning snippets with titles and links. Use this when you need to discover information or find pages matching a query.
+- **Get page**: Retrieves the full content of a specific documentation page by its path. Use this when you already know the page path, such as from search results, and need the complete content rather than a snippet.
+
+AI applications determine when to use each tool based on the context of the conversation. For example, an AI application might first search your documentation to find relevant pages, then use the get page tool to retrieve the full content of the most relevant result.
+
 ### Search parameters
 
 The MCP search tool supports optional parameters that AI applications use to control and refine search results.
@@ -35,6 +44,12 @@ The MCP search tool supports optional parameters that AI applications use to con
 
 AI applications determine when to apply these parameters based on the context of the user's query. For example, if a user asks about a specific API version, the AI application may automatically apply the appropriate filter to provide more relevant results.
 
+### Get page parameters
+
+The get page tool accepts one required parameter:
+
+- **`page`**: The page path to retrieve, such as `'api-reference/create-customer'`. Use page paths returned from search results.
+
 ### MCP compared to web search
 
 AI tools can search the web, but MCP provides distinct advantages for documentation.
@@ -96,7 +111,10 @@ To protect availability, Mintlify applies rate limits to MCP servers.
 | Scope | Limit | Description |
 | :---- | :---- | :---------- |
 | Per user (IP address) | 5,000 requests per hour | Limits how frequently a single user can query your MCP server configuration. |
-| Per documentation site (domain) | 10,000 requests per hour | Limits total searches across all users of your MCP server. |
+| Search per documentation site (domain) | 10,000 requests per hour | Limits total search tool calls across all users of your MCP server. |
+| Get page per documentation site (domain) | 10,000 requests per hour | Limits total get page tool calls across all users of your MCP server. |
+| Authenticated search per documentation site (domain) | 5,000 requests per hour | Limits total authenticated search tool calls across all users of your MCP server. |
+| Authenticated get page per documentation site (domain) | 5,000 requests per hour | Limits total authenticated get page tool calls across all users of your MCP server. |
 
 ## Content filtering and indexing