DecileHub MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Check Decilehub Status, Get Company, Get Filing Report, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add DecileHub as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The DecileHub app connector for LlamaIndex is a standout in the Business Intelligence category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to DecileHub. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in DecileHub?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About DecileHub MCP Server
Connect your DecileHub account to any AI agent and take full control of your venture capital and private equity fund operations through natural conversation.
LlamaIndex agents combine DecileHub tool responses with indexed documents for comprehensive, grounded answers. Connect 12 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Fund Management — List all funds with AUM, strategy, and vintage year, and inspect individual fund details including commitments and portfolio allocation
- Performance Analytics — Retrieve IRR, TVPI, DPI, and benchmark comparisons for any fund
- Portfolio Companies — Browse all portfolio companies with valuations, fund allocations, and investment round history
- Valuation Tracking — Access historical valuation marks and unrealized value changes over time for each portfolio company
- LP Management — List limited partners with commitment amounts, distributions, and allocation profiles
- Regulatory Compliance — Browse and download regulatory filings and compliance reports
The DecileHub MCP Server exposes 12 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 DecileHub tools available for LlamaIndex
When LlamaIndex connects to DecileHub through Vinkius, your AI agent gets direct access to every tool listed below — spanning venture-capital, fund-management, portfolio-analytics, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Verify connectivity
Get company details
Get filing report
Get fund details
Get fund performance
Get investor details
List companies by fund
List filings
List funds
List investors (LPs)
List portfolio companies
List company valuations
Connect DecileHub to LlamaIndex via MCP
Follow these steps to wire DecileHub into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the DecileHub MCP Server
LlamaIndex provides unique advantages when paired with DecileHub through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine DecileHub tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain DecileHub tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query DecileHub, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what DecileHub tools were called, what data was returned, and how it influenced the final answer
DecileHub + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the DecileHub MCP Server delivers measurable value.
Hybrid search: combine DecileHub real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query DecileHub to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying DecileHub for fresh data
Analytical workflows: chain DecileHub queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for DecileHub in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with DecileHub immediately.
"Show the performance metrics for our Fund III and compare against industry benchmarks."
"List all portfolio companies in Fund II and show their current valuations."
"Show me all our LPs and their total commitments across all funds."
Troubleshooting DecileHub MCP Server with LlamaIndex
Common issues when connecting DecileHub to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDecileHub + LlamaIndex FAQ
Common questions about integrating DecileHub MCP Server with LlamaIndex.