Melo MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Melo as an MCP tool provider through the 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 Melo. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Melo?"
)
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 Melo MCP Server
Connect your Melo account to any AI agent and take full control of your real estate intelligence and on-chain property data through natural conversation.
LlamaIndex agents combine Melo tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the 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
- Property Management — List all properties, search by address, and fetch detailed SKU metadata including on-chain IDs
- Market Insights — Access real-time AI-driven market trends and neighborhood analytics for specific locations
- Transaction Monitoring — Track property sales history and blockchain-native events securely
- Listing Oversight — Enumerate active property listings for sale or rent across different regions
- Portfolio Auditing — Retrieve historical data, price changes, and smart contract metadata for on-chain assets
The Melo MCP Server exposes 10 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 Melo to LlamaIndex via MCP
Follow these steps to integrate the Melo 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 10 tools from Melo
Why Use LlamaIndex with the Melo MCP Server
LlamaIndex provides unique advantages when paired with Melo through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Melo tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Melo tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Melo, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Melo tools were called, what data was returned, and how it influenced the final answer
Melo + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Melo MCP Server delivers measurable value.
Hybrid search: combine Melo real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Melo 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 Melo for fresh data
Analytical workflows: chain Melo queries with LlamaIndex's data connectors to build multi-source analytical reports
Melo MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Melo to LlamaIndex via MCP:
get_market_insights
Get real estate market insights
get_onchain_metadata
Get on-chain metadata
get_property
Get details for a specific property
get_property_history
Get historical data for a property
list_active_listings
List all active property listings
list_neighborhoods
List neighborhoods in a city
list_properties
List real estate properties
list_property_collections
List curated property collections
list_transactions
List real estate transactions
search_properties
Search properties by term
Example Prompts for Melo in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Melo immediately.
"List all active properties in Austin, TX."
"Show market insights for Miami."
"Get transaction history for property ID 987."
Troubleshooting Melo MCP Server with LlamaIndex
Common issues when connecting Melo to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMelo + LlamaIndex FAQ
Common questions about integrating Melo 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 Melo 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 Melo to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.