How to Use the DappRadar (Web3 Dapp & NFT Analytics) MCP in CrewAI

Q: How do I pass the DappRadar (Web3 Dapp & NFT Analytics) MCP Server to a CrewAI agent?

You pass your Vinkius HTTP URL directly into the mcps list when defining your agent. For advanced setups, use MCPServerHTTP from the CrewAI library to filter specific tools.

Q: How do I restrict which DappRadar (Web3 Dapp & NFT Analytics) tools my CrewAI agents can use?

Use the toolfilter option within MCPServerHTTP. This lets you restrict access, ensuring your research agent only calls listchains while your analyst agent handles getdappmetrics.

Deploy a collaborative team of CrewAI agents to analyze dapps, chains, and NFT market trends autonomously.

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Connect DappRadar (Web3 Dapp & NFT Analytics) MCP to CrewAI

Create your Vinkius account to connect DappRadar (Web3 Dapp & NFT Analytics) to CrewAI 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 DappRadar (Web3 Dapp & NFT Analytics) with CrewAI

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Coordinate multi-agent Web3 research

The `list_chains` tool gets all active blockchains tracked by DappRadar. Your research agent uses this list to coordinate search tasks, passing specific chain IDs to other specialized agents in your crew. This division of labor keeps your operations clean. One agent identifies the chains, while a second agent calls `get_chain_stats` to compile the final report.

Run autonomous NFT collection audits in CrewAI

The `list_nft_collections` tool pulls ranked collections based on trading volume and sales. Your analyst agent parses this list, then triggers `get_nft_collection_metrics` to deep-dive into specific historical trends. CrewAI manages the shared memory between these agents, ensuring they don't fetch the same NFT data twice. This keeps your runtime efficient and prevents unnecessary API usage.

Monitor dapp performance using this MCP Server

The `get_dapp` tool gets metadata, social links, and active user metrics for any decentralized application. Your monitor agent uses this tool to watch specific dapps and alert a moderator agent if performance drops. Connecting this MCP Server to your crew requires only a single URL in your configuration. You can filter which tools are exposed to keep your agents focused on specific tasks.

Setup guide

Set up DappRadar (Web3 Dapp & NFT Analytics) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke DappRadar (Web3 Dapp & NFT Analytics) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="DappRadar (Web3 Dapp & NFT Analytics) Analyst",
    goal="Access and analyze DappRadar (Web3 Dapp & NFT Analytics) data via MCP.",
    backstory="Expert analyst with direct DappRadar (Web3 Dapp & NFT Analytics) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent DappRadar (Web3 Dapp & NFT Analytics) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="DappRadar (Web3 Dapp & NFT Analytics) Analyst",
        goal="Access and analyze DappRadar (Web3 Dapp & NFT Analytics) data via MCP.",
        backstory="Expert analyst with direct DappRadar (Web3 Dapp & NFT Analytics) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent DappRadar (Web3 Dapp & NFT Analytics) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DappRadar. 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 DappRadar (Web3 Dapp & NFT Analytics) MCP in CrewAI

You pass your Vinkius HTTP URL directly into the `mcps` list when defining your agent. For advanced setups, use `MCPServerHTTP` from the CrewAI library to filter specific tools.

Yes. CrewAI agents share memory, so if your research agent pulls a list using `list_dapps`, your analyst agent can immediately read those results to run detailed queries.

Use the `tool_filter` option within `MCPServerHTTP`. This lets you restrict access, ensuring your research agent only calls `list_chains` while your analyst agent handles `get_dapp_metrics`.

The framework supports stdio, SSE, and streamable HTTP transports. This flexibility makes it easy to deploy your automated crew in local environments or cloud containers.

Yes, the integration runs inside secure, isolated sandboxes. Your target dapp names, contract addresses, and query history remain private and are deleted immediately after execution.

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