MCP

MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems. For more information, please refer to the MCP documentation.

Compatible with both Cursor and Claude Desktop!
Modellix Docs MCP is also compatible with any MCP client.

Modellix Docs MCP provides a search tool for your AI application to initiate search requests within the Modellix documentation.

Remote Server

The easiest way to take advantage of Modellix Docs MCP is by using the remote URL. This provides a seamless experience without requiring local installation or configuration. Simply use the remote MCP server URL:

https://docs.modellix.ai/mcp

Connect to Clients

How to connect Modellix Docs MCP to clients

You can also connect Modellix Docs MCP to popular coding AI tools like Cursor and VS Code with just one click. Find the “Copy Page” menu on the right side of the title on each documentation page, where you’ll find buttons to connect to Cursor and VS Code with one click.

with Smithery

You can also connect to Modellix Docs MCP on Smithery.

with MCP.so

You can also connect to Modellix Docs MCP on MCP.so.

OpenAI

Allow models to use remote MCP servers to perform tasks.

from openai import OpenAI

client = OpenAI()

resp = client.responses.create(
    model="gpt-4.1",
    tools=[
        {
            "type": "mcp",
            "server_label": "modellix-docs",
            "server_url": "https://docs.modellix.ai/mcp",
            "require_approval": "never",
        },
    ],
    input="Do you have access to the modellix docs mcp server?",
)

print(resp.output_text)

How It Works

Once your AI application integrates with Modellix Docs MCP, it can directly search the Modellix documentation instead of performing a generic web search when responding to user prompts. Modellix Docs MCP provides access to all indexed content on the documentation site.

AI applications can proactively search Modellix documentation while generating responses, not just when explicitly requested.
AI applications decide when to use the search tool based on the conversation context and the relevance of Modellix documentation to the current topic.
Each search (tool call) occurs during the generation process, so AI applications retrieve the latest information from Modellix documentation to generate responses.

The MCP search tool supports optional filter parameters that AI applications can use to narrow down search results.

Field Name	Description
`version`	Filter results to a specific documentation version. For example, `v0.7`. Only returns content with the specified version tag, or content that is common across all versions.
`language`	Filter results to a specific language code. For example, `en`, `zh`, or `es`. Only returns content in the specified language, or content that is common across all languages.
`apiReferenceOnly`	When set to true, only returns API reference documentation pages.
`codeOnly`	When set to true, only returns code snippets and examples.

AI applications decide when to apply these filters based on the context of the user’s query. For example, if a user asks about a specific API version or requests code examples, the AI application may automatically apply the appropriate filters to provide more relevant results.

Getting Started

Ways to Use

Remote Server

Connect to Clients

with Smithery

with MCP.so

OpenAI

How It Works

Search Filter Parameters

​Remote Server

​Connect to Clients

​with Smithery

​with MCP.so

​OpenAI

​How It Works

​Search Filter Parameters

Remote Server

Connect to Clients

with Smithery

with MCP.so

OpenAI

How It Works

Search Filter Parameters