How to Use the DecileHub MCP in LlamaIndex

Q: How do I set up the DecileHub MCP Server with LlamaIndex?

Grab the llama-index-tools-mcp package. Create a BasicMCPClient with your endpoint URL, wrap it in an McpToolSpec, and call totoollistasync(). Feed those into your FunctionAgent.

Q: Can LlamaIndex index DecileHub investor lists?

Absolutely. You can execute listinvestors and pipe the resulting JSON directly into your document store. The framework handles the chunking and embedding automatically.

Q: Does DecileHub support LlamaIndex data filters?

You can restrict access using the allowedtools parameter. If you only want the agent reading public filings, just expose the filing tools and block the valuation endpoints.

Index DecileHub fund data into LlamaIndex to build searchable knowledge bases of your private market investments.

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Connect DecileHub MCP to LlamaIndex

Create your Vinkius account to connect DecileHub 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 DecileHub with LlamaIndex

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Index LlamaIndex portfolio data

This MCP Server feeds raw portfolio data directly into your LlamaIndex knowledge base. LlamaIndex takes the output from the endpoints and embeds it into your vector store. You run `list_portfolio_companies`, and those records become instantly queryable documents. Ground your answers in reality. Instead of hoping the model remembers a startup's sector, your RAG application retrieves the exact profile using `get_company`. The system cites the actual data source in its response.

Vectorize fund performance

Vectorize your fund performance metrics by connecting this server. Call `get_fund_performance` to pull the latest metrics, then let LlamaIndex chunk and index the results. Your team can ask plain English questions about IRR or multiples. The integration spans the entire fund structure. You can map out relationships by feeding `list_funds` and `list_companies_by_fund` into your graph database. Complex entity relationships become simple semantic searches.

Search regulatory filings

Index massive regulatory documents by pointing this MCP Server at your filing repository. Use `list_filings` to pull the metadata, then grab the meat of the documents with `get_filing_report`. LlamaIndex turns those massive text blocks into searchable nodes. When an auditor asks for specific disclosures, you just query your index. The system finds the exact paragraph buried in a 200-page filing. No more control-F marathons through PDFs.

Setup guide

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

Grab the `llama-index-tools-mcp` package. Create a `BasicMCPClient` with your endpoint URL, wrap it in an `McpToolSpec`, and call `to_tool_list_async()`. Feed those into your `FunctionAgent`.

Absolutely. You can execute `list_investors` and pipe the resulting JSON directly into your document store. The framework handles the chunking and embedding automatically.

You can restrict access using the `allowed_tools` parameter. If you only want the agent reading public filings, just expose the filing tools and block the valuation endpoints.

The MCP protocol provides semantic descriptions for every function. When a user asks about a specific LP, the router knows to trigger `get_investor` instead of guessing.

Vinkius routes traffic through zero-trust infrastructure. Your historical fund returns and IRR data pass through a secure, single-use container. We handle the authentication centrally, so you never expose raw API keys in your RAG pipeline.

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