How to Use the SuperTokens MCP in LlamaIndex

Q: Does LlamaIndex support SuperTokens authentication data?

Yes. You can index results from calls like getuser or listroles. This allows the LLM to reference specific user details when answering a query.

Q: Can I query user roles using SuperTokens and LlamaIndex?

Absolutely. By indexing the output of listuserroles, you can ask semantic questions about a user's permissions without needing to write specific API calls every time.

Q: How do I use SuperTokens with LlamaIndex to validate history?

You can run a series of API calls (e.g., getuser followed by updateusermetadata) and index the results together. This creates a chronological record you can query later.

Build knowledge graphs for LlamaIndex by indexing SuperTokens API data.

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Setup SuperTokens with LlamaIndex

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Indexing User State with MCP Server

When your agent runs an operation, the output becomes searchable knowledge. You can run `get_user` or `get_user_metadata`, and LlamaIndex indexes those results. This means you can query past API calls later. Instead of guessing, the LLM grounds its answer in actual user records retrieved from the SuperTokens MCP Server.

Retrieving Role History for LlamaIndex

The server exposes `list_user_roles`, which gives you a list of roles assigned to an ID. If this output is indexed, you can ask complex questions like: 'What were the available roles for user X last month?' The RAG application combines live API data with documents, making your knowledge base far more accurate.

Tracking Account Changes via LlamaIndex

When accounts are linked or unlinked, you use the `link_accounts` and `unlink_accounts` tools. Indexing these results lets users query operational history. This ability to search API actions prevents hallucinations; you get answers grounded in verifiable SuperTokens system logs.

Setup guide

Set up SuperTokens 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 SuperTokens 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 SuperTokens tools.",
)
response = await agent.run("List recent SuperTokens data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by SuperTokens. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about SuperTokens MCP in LlamaIndex

Yes. You can index results from calls like `get_user` or `list_roles`. This allows the LLM to reference specific user details when answering a query.

The output of any MCP tool call, such as creating a session via `create_session`, becomes an indexed document. Your RAG application queries this data store for answers.

Absolutely. By indexing the output of `list_user_roles`, you can ask semantic questions about a user's permissions without needing to write specific API calls every time.

The server handles identity, including account credentials and associated metadata. This is the core data that gets indexed into your searchable knowledge base.

You can run a series of API calls (e.g., `get_user` followed by `update_user_metadata`) and index the results together. This creates a chronological record you can query later.

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