How to Use the Glassnode (On-chain Data) MCP in CrewAI

Q: How do I limit Glassnode (On-chain Data) tools for a CrewAI agent?

Use the toolfilter option in your configuration. This allows you to expose only the necessary functions to specific agents in the crew.

Deploy a specialized crew to monitor market flows with CrewAI and the Glassnode (On-chain Data) MCP Server.

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Connect Glassnode (On-chain Data) MCP to CrewAI

Create your Vinkius account to connect Glassnode (On-chain Data) 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 Glassnode (On-chain Data) with CrewAI

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Multi-agent research with CrewAI

Assign an analyst agent to monitor `get_metric` streams while another agent manages the trade execution. CrewAI distributes the workload across your crew. Each agent focuses on one aspect of the data. This division of labor ensures your pipeline remains organized and efficient during high-volume periods.

Selective tool filtering for CrewAI

Restrict your agents to specific tools using `list_metrics` and `get_metric_details`. This prevents agents from querying data they don't need. By limiting access, you keep your CrewAI agents focused. They only interact with the data points relevant to their specific role in the team.

Autonomous monitoring via CrewAI

Set up a monitor agent that continuously checks for anomalies using `get_bulk_metric`. Your crew stays alert for market shifts without you watching the screen. When the agent detects a specific pattern, it signals the rest of the team to take action. It is a fully autonomous observation loop.

Setup guide

Set up Glassnode (On-chain Data) 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 Glassnode (On-chain Data) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Glassnode (On-chain Data) 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 Glassnode. 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 Glassnode (On-chain Data) MCP in CrewAI

Use the tool_filter option in your configuration. This allows you to expose only the necessary functions to specific agents in the crew.

Yes. Agents can share insights derived from the metrics, allowing them to collaborate on complex market analysis tasks.

Yes. You can assign the data retrieval tools to a manager agent that delegates specific queries to subordinate researchers.

Yes. It supports stdio, SSE, and Streamable HTTP, giving you flexibility in how your agents connect to the server.

Your access token is kept in a local environment variable. The server only sees the authenticated request, keeping your credentials hidden from the agent environment.

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