How to Use the Arweave MCP in CrewAI

Q: Can CrewAI agents cooperate on Arweave tasks?

Absolutely. One agent can query the network with querygraphql and pass the results to a second agent to act on that information.

Q: What happens if Arweave storage prices change?

Your agents can poll getstorageprice before every submission. This ensures your budget stays intact as network fees fluctuate.

Deploy a CrewAI team to monitor Arweave network health and manage permanent storage operations autonomously.

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Connect Arweave MCP to CrewAI

Create your Vinkius account to connect Arweave 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 Arweave with CrewAI

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Autonomous network monitoring teams

Assign a researcher agent to run `get_network_info` and `get_peers`. It watches the permaweb and reports changes to the rest of the crew. This keeps your operations running without human intervention. Your crew reacts to network shifts immediately.

Collaborative transaction analysis

Let one agent fetch transaction data with `get_transaction` while another audits it. They share memory to refine the findings. This removes the need for manual review. Your agents handle the verification process from start to finish.

Automated archival workflows

Use a specialized agent to calculate costs with `get_storage_price` and submit data via `submit_transaction`. It handles the math and the execution. This creates a hands-off archival system. You set the policy, and the crew manages the permaweb storage.

Setup guide

Set up Arweave 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 Arweave tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Arweave 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 Arweave. 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 Arweave MCP in CrewAI

Pass the server URL directly to the agent's MCP configuration. The framework handles the connection so your agents can start using the tools immediately.

Absolutely. One agent can query the network with `query_graphql` and pass the results to a second agent to act on that information.

The tools provide exact status updates. You can build a monitor agent that specifically tracks `get_transaction_status` to confirm finality.

Your agents can poll `get_storage_price` before every submission. This ensures your budget stays intact as network fees fluctuate.

The server transmits data to the public blockchain. Any logs handled by the agents should be treated as public, immutable records.

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