How do I find my Melo API Key?

Log in to Melo, go to your Dashboard settings, and look for the API section to generate or copy your key.

What is 'on-chain' property data?

This refers to real estate information recorded on a blockchain, providing a transparent and immutable history of ownership and events.

Is my real estate data secure?

Absolutely. Your token is encrypted at rest and injected securely at runtime.

Melo MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Melo
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Melo through Vinkius, pass the Edge URL in the `mcps` parameter and every Melo tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Melo Specialist",
    goal="Help users interact with Melo effectively",
    backstory=(
        "You are an expert at leveraging Melo tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Melo "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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High SecurityEnterprise-grade

IAMAccess control

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Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

When paired with CrewAI, Melo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Melo tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Melo MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Melo

Why Use CrewAI with the Melo MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Melo through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Melo + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Melo MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Melo for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Melo, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Melo tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Melo against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Melo MCP Tools for CrewAI (10)

These 10 tools become available when you connect Melo to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Melo to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Melo + CrewAI FAQ

Common questions about integrating Melo MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.