How to Use the Corsizio MCP in LlamaIndex

Q: Can I filter Corsizio tools in LlamaIndex?

You can use an allowedtools filter during setup. This restricts which parts of your account the agent can query.

Index your Corsizio event data directly into LlamaIndex knowledge bases.

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Connect Corsizio MCP to LlamaIndex

Create your Vinkius account to connect Corsizio 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 Corsizio with LlamaIndex

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Search Corsizio logs with LlamaIndex

Tool outputs from `list_events` get indexed into your vector store immediately. You query your own event history using natural language instead of digging through dashboard menus. This creates a grounded knowledge base for your RAG pipeline. The agent pulls precise registration data from the index rather than guessing event dates.

Map attendee history for LlamaIndex

Use `list_attendees` to build a semantic map of your user base. LlamaIndex treats these results as searchable documents for your retrieval tasks. Run `get_attendee_details` to add specific payment history to the index. Your agent provides answers based on the actual registration profile stored in your account.

Query Corsizio financial records

Your agent calls `list_payments` and maps the transaction data into your knowledge index. You ask questions about refund trends and get answers based on the raw ledger. This turns your static transaction history into an active resource. LlamaIndex links these payments to specific events identified by the `get_event_details` tool.

Setup guide

Set up Corsizio 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 Corsizio 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 Corsizio tools.",
)
response = await agent.run("List recent Corsizio 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 Corsizio. 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 Corsizio MCP in LlamaIndex

Use the MCP tool spec to wrap the client. Once connected, your agent converts the tool list into a format LlamaIndex can index.

By indexing the output, you ground the agent in reality. It reads the actual API response and incorporates that data into its knowledge base.

You can use an allowed_tools filter during setup. This restricts which parts of your account the agent can query.

Every request is ephemeral. We process the data in our secure sandbox and never persist your event details on our servers.

It processes event configuration, payment IDs, and attendee contact info. We treat every bit of this as sensitive and isolate it within the runtime.

Use it with your favorite AI tools

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