How to Use the Kinde (Modern Authentication) MCP in LlamaIndex

Q: How do I configure Kinde (Modern Authentication) inside LlamaIndex?

Install llama-index-tools-mcp and instantiate a BasicMCPClient with your endpoint. Wrap it in McpToolSpec to expose the identity tools to your query engine.

Q: Can LlamaIndex search through Kinde (Modern Authentication) roles?

It handles this natively. The agent calls listroles, indexes the returned JSON, and lets you run semantic queries against the role descriptions.

Q: How do I restrict which Kinde (Modern Authentication) tools LlamaIndex can access?

Use the allowedtools filter when converting the MCP tool spec. You can expose getuser for read-only queries while blocking createuser to prevent accidental provisioning.

Index your identity provider. Let LlamaIndex query Kinde user states and organization structures directly to ground your RAG applications.

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Connect Kinde (Modern Authentication) MCP to LlamaIndex

Create your Vinkius account to connect Kinde (Modern Authentication) 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 Kinde (Modern Authentication) with LlamaIndex

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Indexing Kinde Data in LlamaIndex

Stop guessing who has access to what in Kinde. LlamaIndex pulls live data using `list_users` and `list_organizations` via the MCP Server, converting your entire identity directory into searchable documents. When you ask your RAG application about team structures, it doesn't hallucinate. It reads the indexed API responses and tells you exactly which accounts exist in the current Kinde environment.

Semantic Search for Permissions

Finding the right role in a massive system is tedious. By running `list_roles` and `list_permissions`, the agent ingests your access control matrix into a vector store. You just type a query asking for billing admin capabilities. The LlamaIndex query engine searches the indexed tools, finds the matching role IDs, and returns the exact string needed for assignment.

Context-Aware User Updates

Agents need context before altering accounts. Your application can run `get_user` to pull a specific profile into the active context window. Once the current state is loaded, the agent evaluates the requested changes against your internal policy documents. If everything checks out, it fires `update_user` to apply the modifications safely.

Setup guide

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

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Common questions about Kinde (Modern Authentication) MCP in LlamaIndex

Install `llama-index-tools-mcp` and instantiate a `BasicMCPClient` with your endpoint. Wrap it in `McpToolSpec` to expose the identity tools to your query engine.

It handles this natively. The agent calls `list_roles`, indexes the returned JSON, and lets you run semantic queries against the role descriptions.

Yes. Your RAG agent can read an onboarding document, extract the company details, and execute `create_organization` to set up the workspace automatically.

Use the `allowed_tools` filter when converting the MCP tool spec. You can expose `get_user` for read-only queries while blocking `create_user` to prevent accidental provisioning.

This integration handles sensitive PII, including email addresses and authentication IDs. LlamaIndex stores this information locally in your vector database, keeping user profiles out of third-party cloud logs.

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