Glassnode (On-chain Data) MCP Server for CrewAIGive CrewAI instant access to 6 tools to Get Bulk Metric, Get Metric, Get Metric Details, and more

Name: Glassnode (On-chain Data)
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

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

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The Glassnode (On-chain Data) MCP Server for CrewAI is a standout in the Data Analytics category — giving your AI agent 6 tools to work with, ready to go from day one.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Glassnode (On-chain Data) Specialist",
    goal="Help users interact with Glassnode (On-chain Data) effectively",
    backstory=(
        "You are an expert at leveraging Glassnode (On-chain Data) 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 Glassnode (On-chain Data) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

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

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About Glassnode (On-chain Data) MCP Server

Connect your Glassnode account to any AI agent to analyze crypto markets with precision. Fetch real-time and historical on-chain metrics, exchange flows, and network health data through natural conversation.

When paired with CrewAI, Glassnode (On-chain Data) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Glassnode (On-chain Data) 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

Asset Discovery — List all supported assets and blockchains using list_assets to identify available data points.
Metric Exploration — Query thousands of metric paths with list_metrics and get detailed documentation on parameters via get_metric_details.
Time-Series Analysis — Retrieve historical data for active addresses, exchange balances, and price metrics using get_metric.
Bulk Data — Fetch metrics for multiple assets simultaneously with get_bulk_metric to compare market trends.
Point-in-Time Data — Access immutable historical snapshots via get_pit_metric to eliminate look-ahead bias in backtesting.

The Glassnode (On-chain Data) MCP Server exposes 6 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 6 Glassnode (On-chain Data) tools available for CrewAI

When CrewAI connects to Glassnode (On-chain Data) through Vinkius, your AI agent gets direct access to every tool listed below — spanning on-chain-data, market-intelligence, crypto-analytics, 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 bulk metric on Glassnode (On-chain Data)

Use a="*" for all assets. Get bulk metric data for multiple assets

get

Get metric on Glassnode (On-chain Data)

Path should be the metric name like "addresses/active_count" or "market/price_usd_close". Get time-series data for a specific metric

get

Get metric details on Glassnode (On-chain Data)

Get details, allowed parameters, and description for a specific metric

get

Get pit metric on Glassnode (On-chain Data)

Get Point-in-Time (PIT) metric data

list

List assets on Glassnode (On-chain Data)

List all supported assets on Glassnode

list

List metrics on Glassnode (On-chain Data)

Can be filtered by asset, interval, etc. List all available metric paths on Glassnode

Connect Glassnode (On-chain Data) to CrewAI via MCP

Follow these steps to wire Glassnode (On-chain Data) 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 6 tools from Glassnode (On-chain Data)

Why Use CrewAI with the Glassnode (On-chain Data) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Glassnode (On-chain Data) 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

Glassnode (On-chain Data) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Glassnode (On-chain Data) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Glassnode (On-chain Data) 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 Glassnode (On-chain Data), analyzes trends over time, and generates executive briefings in markdown or PDF format

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

Example Prompts for Glassnode (On-chain Data) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Glassnode (On-chain Data) immediately.

"List all supported assets on Glassnode."

"Get the 'addresses/active_count' metric for BTC from the last 7 days with a 24h interval."

"Show me the details and allowed parameters for the metric path 'market/price_usd_close'."

Troubleshooting Glassnode (On-chain Data) MCP Server with CrewAI

Common issues when connecting Glassnode (On-chain Data) 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.

Glassnode (On-chain Data) + CrewAI FAQ

Common questions about integrating Glassnode (On-chain Data) 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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