How to Use the Document360 MCP in LlamaIndex

Q: How do I search my Document360 docs using LlamaIndex?

You integrate the search tool as a function in your agent. It takes your query and returns the relevant articles as context for your retrieval process.

Q: Does LlamaIndex automatically track Document360 changes?

The agent can be set up to poll using listarticles. If you detect a change in the metadata, the agent triggers an update to your local index.

Q: Can I query Document360 project versions with LlamaIndex?

Yes, the listprojects tool lets your agent see every available version. You can then select the specific version to index for your current task.

Q: How are Document360 team details handled?

The listteam tool returns account info. You can use this to attribute documentation ownership or identify who to contact for article updates.

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Connect Document360 MCP to LlamaIndex

Create your Vinkius account to connect Document360 to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Document360 with LlamaIndex

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Index Document360 articles in LlamaIndex

Pipe content from `get_article` straight into your vector store. Your index stays current because the agent pulls the latest text directly from the source. It grounds your model in actual documentation. You stop dealing with outdated information and rely on the live state of your knowledge base.

Semantic search across your documentation

Use the `search` tool to perform targeted queries that inform your RAG pipeline. It retrieves the most relevant articles based on your specific user intent. Your index becomes much smarter. By feeding search results back into your pipeline, you ensure the model has the right context before it generates a response.

Navigate versions via MCP server tools

Use `list_projects` and `list_categories` to define the scope of your indexing. You control exactly which parts of the documentation the agent explores. It prevents data bloat. You only index what you need, making your retrieval faster and your answers more precise.

Setup guide

Set up Document360 MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Document360 MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Document360 tools.",
)
response = await agent.run("List recent Document360 data")

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Common questions about Document360 MCP in LlamaIndex

You integrate the `search` tool as a function in your agent. It takes your query and returns the relevant articles as context for your retrieval process.

The agent can be set up to poll using `list_articles`. If you detect a change in the metadata, the agent triggers an update to your local index.

Yes, the `list_projects` tool lets your agent see every available version. You can then select the specific version to index for your current task.

It accesses your article text, category labels, project metadata, and analytics reports. All data is handled through your single-use endpoint token.

The `list_team` tool returns account info. You can use this to attribute documentation ownership or identify who to contact for article updates.

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