NCREIF Custom Query MCP Server for LlamaIndex 3 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add NCREIF Custom Query 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 MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 NCREIF Custom Query. "
"You have 3 tools available."
),
)
response = await agent.run(
"What tools are available in NCREIF Custom Query?"
)
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 NCREIF Custom Query MCP Server
Empower your AI agents with institutional real estate intelligence. This server provides programmatic access to the NCREIF Query Tool API, allowing for deep analysis of the NCREIF Property Index (NPI), Fund Index (ODCE), and specialized timberland/farmland data.
LlamaIndex agents combine NCREIF Custom Query tool responses with indexed documents for comprehensive, grounded answers. Connect 3 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
- Custom Analytics — Execute SQL-like queries to calculate income returns, appreciation, and total returns
- Index Monitoring — Access historical and real-time performance data for major US real estate indices
- Predefined KPIs — Quickly retrieve key metrics like Cap Rates and Occupancy percentages
- Granular Filtering — Filter by property type, region, CBSA, and more using powerful where clauses
The NCREIF Custom Query MCP Server exposes 3 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.
How to Connect NCREIF Custom Query to LlamaIndex via MCP
Follow these steps to integrate the NCREIF Custom Query MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 3 tools from NCREIF Custom Query
Why Use LlamaIndex with the NCREIF Custom Query MCP Server
LlamaIndex provides unique advantages when paired with NCREIF Custom Query through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine NCREIF Custom Query tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain NCREIF Custom Query tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query NCREIF Custom Query, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what NCREIF Custom Query tools were called, what data was returned, and how it influenced the final answer
NCREIF Custom Query + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the NCREIF Custom Query MCP Server delivers measurable value.
Hybrid search: combine NCREIF Custom Query real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query NCREIF Custom Query 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 NCREIF Custom Query for fresh data
Analytical workflows: chain NCREIF Custom Query queries with LlamaIndex's data connectors to build multi-source analytical reports
NCREIF Custom Query MCP Tools for LlamaIndex (3)
These 3 tools become available when you connect NCREIF Custom Query to LlamaIndex via MCP:
execute_query
Execute a custom NCREIF query
get_historical_npi
Get historical NPI returns
get_predefined_kpi
Get predefined KPI data
Example Prompts for NCREIF Custom Query in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with NCREIF Custom Query immediately.
"Show NPI total returns for the last 4 quarters."
Troubleshooting NCREIF Custom Query MCP Server with LlamaIndex
Common issues when connecting NCREIF Custom Query to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpNCREIF Custom Query + LlamaIndex FAQ
Common questions about integrating NCREIF Custom Query MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect NCREIF Custom Query with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect NCREIF Custom Query to LlamaIndex
Get your token, paste the configuration, and start using 3 tools in under 2 minutes. No API key management needed.