DefiLlama (DeFi Analytics) MCP Server for CrewAIGive CrewAI instant access to 19 tools to Get All Bridges, Get All Chains Tvl, Get All Pools, and more

Name: DefiLlama (DeFi Analytics)
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The DefiLlama (DeFi Analytics) MCP Server for CrewAI is a standout in the Data Analytics category — giving your AI agent 19 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="DefiLlama (DeFi Analytics) Specialist",
    goal="Help users interact with DefiLlama (DeFi Analytics) effectively",
    backstory=(
        "You are an expert at leveraging DefiLlama (DeFi Analytics) 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 DefiLlama (DeFi Analytics) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 19 available tools "
        "and what they can do."
    ),
)

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

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

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 DefiLlama (DeFi Analytics) MCP Server

Connect your AI agent to DefiLlama, the leading aggregator for decentralized finance data. This server allows you to query real-time and historical metrics across the entire DeFi ecosystem through natural conversation.

When paired with CrewAI, DefiLlama (DeFi Analytics) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call DefiLlama (DeFi Analytics) 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

TVL Analytics — Track Total Value Locked (TVL) for specific protocols, individual chains, or the global DeFi market.
Token Pricing — Retrieve current and historical prices, generate price charts, and calculate percentage changes for thousands of tokens.
Yield & Pools — Monitor APY and TVL for liquidity pools to identify the best yield farming opportunities.
Volume & Liquidity — Analyze DEX volumes, bridge activity, and stablecoin market caps across different ecosystems.
Historical Deep-Dives — Access time-series data to understand market trends and protocol growth over time.

The DefiLlama (DeFi Analytics) MCP Server exposes 19 tools through the Vinkius. Connect it to CrewAI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 19 DefiLlama (DeFi Analytics) tools available for CrewAI

When CrewAI connects to DefiLlama (DeFi Analytics) through Vinkius, your AI agent gets direct access to every tool listed below — spanning defi, tvl, crypto-prices, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get all bridges on DefiLlama (DeFi Analytics)

Get all bridges

get

Get all chains tvl on DefiLlama (DeFi Analytics)

Get current TVL for all chains

get

Get all pools on DefiLlama (DeFi Analytics)

Get current APY and TVL for all pools

get

Get all stablecoins on DefiLlama (DeFi Analytics)

Get all stablecoins

get

Get bridge volume chain on DefiLlama (DeFi Analytics)

Get bridge volume for a specific chain

get

Get current prices on DefiLlama (DeFi Analytics)

Format: {chain}:{address} Get the current price of tokens

get

Get current tvl chain on DefiLlama (DeFi Analytics)

Get the current total TVL for a specific chain

get

Get dex volume chain on DefiLlama (DeFi Analytics)

Get DEX volume for a specific chain

get

Get dex volumes global on DefiLlama (DeFi Analytics)

Get DEX volumes globally

get

Get historical prices on DefiLlama (DeFi Analytics)

Get the price of tokens at a specific timestamp

get

Get historical tvl chain on DefiLlama (DeFi Analytics)

Get historical TVL for a specific blockchain

get

Get historical tvl global on DefiLlama (DeFi Analytics)

Get historical TVL of the entire DeFi ecosystem

get

Get percentage change on DefiLlama (DeFi Analytics)

Get the price change over a period

get

Get pool historical data on DefiLlama (DeFi Analytics)

Get historical APY and TVL for a specific pool

get

Get price chart on DefiLlama (DeFi Analytics)

Get a chart of token prices over time

get

Get protocol on DefiLlama (DeFi Analytics)

Get historical TVL data for a specific protocol

get

Get protocols on DefiLlama (DeFi Analytics)

Get all protocols on DefiLlama along with their current TVL

get

Get stablecoin historical data on DefiLlama (DeFi Analytics)

Get stablecoin historical data

get

Get stablecoin market cap chain on DefiLlama (DeFi Analytics)

Get stablecoin market cap for a specific chain

Connect DefiLlama (DeFi Analytics) to CrewAI via MCP

Follow these steps to wire DefiLlama (DeFi Analytics) into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 19 tools from DefiLlama (DeFi Analytics)

Why Use CrewAI with the DefiLlama (DeFi Analytics) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with DefiLlama (DeFi Analytics) 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

DefiLlama (DeFi Analytics) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the DefiLlama (DeFi Analytics) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries DefiLlama (DeFi Analytics) 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 DefiLlama (DeFi Analytics), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain DefiLlama (DeFi Analytics) 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 DefiLlama (DeFi Analytics) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for DefiLlama (DeFi Analytics) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with DefiLlama (DeFi Analytics) immediately.

"List all DeFi protocols and their current TVL."

"What is the current TVL on the Arbitrum chain?"

"Show me the price chart for USDC on Ethereum."

Troubleshooting DefiLlama (DeFi Analytics) MCP Server with CrewAI

Common issues when connecting DefiLlama (DeFi Analytics) to CrewAI through 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.

DefiLlama (DeFi Analytics) + CrewAI FAQ

Common questions about integrating DefiLlama (DeFi Analytics) 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.

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