How to Use the DefiLlama (DeFi Analytics) MCP in CrewAI

Q: How do I assign DefiLlama (DeFi Analytics) tools to a specific CrewAI agent?

Use MCPServerHTTP from crewai.mcp. Apply a toolfilter so your yield-hunting agent only sees the specific tools it needs, rather than the entire suite.

Q: How do I set up the DefiLlama (DeFi Analytics) MCP Server in CrewAI?

Pass your Vinkius endpoint URL directly into the mcps array when defining your agent. The framework automatically discovers and registers every available operation.

Deploy autonomous CrewAI teams to monitor DeFi yields, track bridge volumes, and analyze protocol health.

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Connect DefiLlama (DeFi Analytics) MCP to CrewAI

Create your Vinkius account to connect DefiLlama (DeFi 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 DefiLlama (DeFi Analytics) with CrewAI

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Perplexity

Build a dedicated research agent.

Giving an agent access to `get_historical_tvl_global` lets it map out the entire ecosystem's growth trajectory. Trying to piece together macro crypto trends by hand takes hours. You can assign a specialized analyst to handle the heavy lifting. Executing `get_all_stablecoins` reveals if fresh capital is actually entering the market. The agent does not just stop at total value locked. Your output is a finished report, not raw JSON.

Automate APY tracking across chains.

Running `get_all_pools` continuously flags any new high-return opportunities. Setting up a monitor agent changes how you find yield. It watches the market so you do not have to. Triggering `get_protocol` checks the underlying dApp's historical TVL. Once it spots a target, a secondary verifier agent steps in. You only get notified when both agents agree the pool is safe and profitable.

Watch liquidity flow via this MCP Server.

Deploying `get_bridge_volume_chain` tracks exactly how much value is crossing between blockchains. Capital rotation happens fast. Your crew needs to spot money moving before the crowd notices. Firing `get_dex_volume_chain` confirms if the bridged capital is actually being traded. Combining that with trading activity provides a massive edge. You get the full picture without clicking through a dozen dashboards.

Setup guide

Set up DefiLlama (DeFi 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 DefiLlama (DeFi Analytics) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent DefiLlama (DeFi 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="DefiLlama (DeFi Analytics) Analyst",
        goal="Access and analyze DefiLlama (DeFi Analytics) data via MCP.",
        backstory="Expert analyst with direct DefiLlama (DeFi Analytics) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent DefiLlama (DeFi 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 DefiLlama. 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 DefiLlama (DeFi Analytics) MCP in CrewAI

Use `MCPServerHTTP` from `crewai.mcp`. Apply a `tool_filter` so your yield-hunting agent only sees the specific tools it needs, rather than the entire suite.

They share context automatically. If your researcher pulls data using `get_all_chains_tvl`, your analyst agent can read those exact numbers from shared memory.

Pass your Vinkius endpoint URL directly into the `mcps` array when defining your agent. The framework automatically discovers and registers every available operation.

Your agents can grab current token prices, historical TVL, bridge volumes, and detailed liquidity pool APYs through the MCP protocol.

We run a zero-trust architecture. When your agent queries specific DEX volumes or bridge flows, that request hits a temporary sandbox. The container and your query data are wiped completely the second the connection drops.

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