Glassnode On-chain Data MCP. Analyze Bitcoin and Ethereum metrics instantly.
Glassnode (On-chain Data) gives your AI client direct access to institutional-grade on-chain metrics for Bitcoin, Ethereum, and over a thousand assets. You can pull real-time exchange flows, network health data, and historical time-series data using natural conversation. It's built for serious crypto research, allowing you to backtest models and compare market trends across multiple digital assets instantly.
Give Claude and any AI agent real-world access
It shows you every asset and blockchain type that can be analyzed.
You get detailed explanations, allowed parameters, and descriptions for specific metrics paths.
It fetches historical trends for any specified on-chain metric over a chosen period.
You can pull the same type of metric across several different digital assets simultaneously to compare market health.
It pulls immutable data points for backtesting, ensuring your analysis avoids looking ahead at future prices.
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What AI agents can do with Glassnode (On-chain Data) MCP: 6 Tools
Use these tools to list supported assets, explore metric documentation, pull time-series data, run bulk comparisons, and access historical snapshots for rigorous crypto analysis.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Glassnode (On-chain Data) MCPGet Bulk Metric
Retrieves a metric across multiple assets at once for comparison.
Get Metric Details
Provides the specific parameters and description for any given on-chain metric path.
Get Metric
Gets a standard time-series data set for one specified metric over time.
Get Pit Metric
Retrieves an immutable historical snapshot of a metric at a specific point in time.
List Assets
Outputs a comprehensive list of all supported cryptocurrencies and assets on...
List Metrics
Lists every available metric path, allowing you to see what data is even measurable.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Glassnode (On-chain Data), then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
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.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The constant struggle of building crypto reports
Today, getting a comprehensive view of market health is a mess. You're forced to open ten different browser tabs—one for Bitcoin flow, one for Ethereum metrics, another for exchange balances, and then maybe two more just to find the correct historical data point. Then you spend an hour copy-pasting numbers from dashboard A into your Excel sheet, manually verifying that they match what dashboard B says.
With this MCP, you talk to your agent once. You ask it for a multi-asset comparison across three metrics—like active addresses and exchange balances. The raw, structured data arrives formatted and ready in the chat window. It's not just faster; it changes what's possible.
Get On-Chain Metrics with Glassnode (On-chain Data)
The process of looking up metrics used to involve jumping through hoops: checking the API documentation, figuring out parameter limits, and writing complex queries just to list available assets. You’d spend half your time on setup and the other half analyzing.
Now, you simply ask. The MCP handles the complexity behind the scenes. It gives you access to institutional-grade data points like exchange flows and network metrics without needing a single line of code or deep API knowledge.
What Glassnode On-chain Data MCP does for your AI
Use this MCP to analyze crypto markets with the precision of institutional tools. Instead of checking ten different dashboards just to track a few key metrics, your AI client fetches everything—from active address counts to specific asset flows—all in one place. You can query thousands of metric paths and pull historical data for any number of assets at once.
It's about getting clean, structured time-series data directly into your chat environment. If you use Vinkius, this MCP integrates that depth of on-chain intelligence right where you’re working with your AI agent. This lets crypto traders monitor whale movements without ever leaving the conversational interface, and it gives data scientists the raw metrics they need for rigorous modeling.
019e389f-fff5-7004-a5a5-af0fbabaac7d How to set up Glassnode On-chain Data MCP
The bottom line is you don't need to manually navigate complex dashboards; your AI client does it for you via conversation.
Subscribe to this MCP and enter your Glassnode API Key.
Direct your AI client to the MCP. Your agent is now ready to receive on-chain data requests.
Ask a question in plain language, like 'What were the active addresses for ETH last month?' and get structured metrics returned.
Who uses Glassnode On-chain Data MCP
Anyone who needs raw, verifiable data about digital asset performance. This is built for the quantitative researcher tired of switching between multiple web portals just to compile a single report.
They use it to run backtests by fetching point-in-time metrics and calculating complex ratios across various assets.
They monitor exchange inflows, tracking large 'whale' movements in real time without leaving their chat interface.
They pull clean, structured time-series data directly into an analysis environment to build predictive models on network growth.
Benefits of connecting Glassnode On-chain Data MCP
Precision Backtesting: Use get_pit_metric to pull historical snapshots, eliminating look-ahead bias when testing trading strategies. You're working with accurate data points, not averages.
Massive Data Comparison: Forget running separate queries for every asset. The get_bulk_metric tool lets you compare market trends across dozens of assets simultaneously in one go.
Instant Documentation Lookup: Need to know what a metric path means? Use get_metric_details to instantly pull parameter rules and descriptions, saving time searching documentation.
Full Asset Coverage: Start by running list_assets to see exactly which assets are available. This ensures you never miss a potential data stream for your analysis.
Robust Time-Series Analysis: The get_metric tool pulls clean historical data—like active address counts or exchange balances—that’s ready to drop straight into a chart or spreadsheet.
Glassnode On-chain Data MCP use cases
Tracking Whale Activity
A trader needs to know if large holders are accumulating BTC. They ask their agent, 'Show me the latest exchange flows for BTC.' The agent uses get_metric and returns a clean time-series graph of inflows/outflows.
Comparing Market Health
A financial analyst wants to compare Ethereum's active addresses against Polygon’s. They use the agent and ask it to fetch data via get_bulk_metric, getting a side-by-side metric comparison instantly.
Historical Modeling
A data scientist needs to test a strategy from Q4 2023. They use get_pit_metric to lock in the exact state of the market for that date, guaranteeing their model runs on immutable data.
Understanding Metrics
A new user doesn't know if 'market/price_usd_close' is correct. They ask the agent to use get_metric_details and receive a detailed explanation of the metric’s parameters and allowed intervals.
Glassnode On-chain Data MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Confusing live data with backtesting
Trying to analyze a trading strategy using the most recent, current metrics because it's easier. This introduces look-ahead bias and gives false signals.
Always use get_pit_metric when simulating past performance. This tool captures an exact snapshot of the market at a specific date, ensuring your backtest is accurate.
Forgetting metric names
Spending 20 minutes searching through documentation to find the exact path for 'daily active addresses.'
First, run list_metrics. This gives you a comprehensive catalog of every possible data point available on Glassnode.
Manual comparison hell
Running five separate queries—one for BTC, one for ETH, one for SOL, etc.—and then manually compiling the results into a spreadsheet.
Use get_bulk_metric. You can ask your agent to gather and present metrics for multiple assets in a single request.
When to use Glassnode On-chain Data MCP
You should use this MCP if your core need is programmatic, verifiable market data. If you're analyzing relationships between assets (e.g., 'How did ETH active addresses correlate with BTC exchange flows?'), or if you are building a quantitative model that requires time-series depth and historical accuracy, this tool is essential. Don't use it just because you want general news or qualitative commentary; the MCP cannot tell you why prices moved, only what they were. If your goal is simply to get a high-level summary report for a client meeting, stick with simple web dashboards. But if that report needs underlying metrics—like active addresses (get_metric) or historical price points (get_pit_metric)—this MCP provides the necessary raw materials.
Frequently asked questions about Glassnode On-chain Data MCP
How do I start getting on-chain data using Glassnode (On-chain Data) MCP? +
First, you need to subscribe and provide your API key. Once connected, simply ask your AI client for the metrics you want; it handles the rest.
Can I use get_bulk_metric if I only care about one asset? +
Yes, you can. While designed for comparison, you can still use it to query a single asset, but listing metrics or using get_metric is often simpler for singular focus.
What is the difference between get_metric and get_pit_metric? +
get_metric pulls standard time-series data (like averages over a period). get_pit_metric provides an immutable snapshot of the market at one precise moment, which is critical for backtesting.
Does list_assets show all assets I can analyze? +
Yes, running list_assets will give you a complete catalog of supported digital assets and blockchains right out of the gate.
What if I need documentation for a metric path? Should I use get_metric_details? +
Yes. Use get_metric_details to understand exactly what a specific metric means, what parameters it accepts, and how it's calculated.