A Practical Guide to Glassnode’s MCP Server

The Glassnode MCP (Model Context Protocol) server brings institutional-grade market intelligence directly into AI workflows, enabling seamless LLM access to Glassnode’s on-chain metrics and market data. This guide focuses on practical use cases that demonstrate how to leverage the server's capabilities for both data discovery and analysis through an LLM chat interface.

Understanding the MCP Server's Capabilities

The Glassnode MCP server provides six specialized tools that work together to create a comprehensive analytics experience:

• Asset and Metrics Discovery: Navigate through 1,700+ supported cryptocurrencies and 900+ metrics
• Metadata Retrieval: Access detailed information about metric parameters and requirements
• Data Fetching: Retrieve both single and bulk historical data with customizable time resolutions and parameters

The Six Tools

1. get_assets_list: Discover all supported assets and tokens across the platform
2. get_metrics_list: Browse the complete catalog of metrics
3. get_asset_metrics: Find all available metrics for a specific asset
4. get_metric_metadata: Retrieve detailed parameters and information for any metric
5. fetch_metric: Fetch data (max 30d history) for a specific metric with customizable parameters
6. fetch_bulk_metrics: Fetch data (max 30d history) for multiple assets simultaneously in a single request

Part 1: Discovery and Exploration

One of the server's primary strengths lies in helping users navigate Glassnode's extensive data catalog. Rather than manually navigating the entire metrics catalog or documentation, users can explore the offerings interactively. Some examples:

Discovering Available Assets and Metrics

When first working with the MCP server, a natural starting point is understanding what's available.

Query: "How many cryptocurrencies does Glassnode support?"

Query: "Which metrics for futures markets does Glassnode support? Show a comprehensive list of all endpoints."

Asset-Specific Metric Discovery

Each asset has a unique set of supported metrics based on its blockchain and market presence.

Query: "Which metrics for Solana are available?"

Understanding Metric Metadata and Parameters

Before fetching data, it's crucial to understand what parameters each metric supports.

Query: "Which resolutions are supported for BTC exchange balance metrics? Is a point-in-time variant available?"

Exploring On-Chain Activity Metrics

Query: "What on-chain activity metrics can I track for Ethereum?"

Understanding Profit/Loss Segmentation

Query: "What profit/loss metrics are available across different holder cohorts?"

Exploring DeFi Protocol Metrics

Query: "Can I track DeFi protocol metrics like Aave or Uniswap?"

Part 2: Data Analysis

Beyond discovery, the MCP server enables retrieving and analyzing current metric data (up to 30 days of history). Here are practical examples demonstrating its capabilities.

Comparing Derivatives Markets

Query: "How does the futures open interest between BTC and ETH compare over the last week?"

Tracking ETF Flows

Query: "How much Bitcoin has flowed into/out of ETFs in the recent month?"

Analyzing Wealth Distribution

Query: "How many addresses currently hold more than $1 million worth of BTC? How has this changed in the past week?"

Multi-Asset Comparison

Query: "Plot the funding rates for BTC, ETH, and SOL to compare current market sentiment"

Exchange Balance Dynamics

Query: "What's the current trend in exchange balances for major BTC and ETH?"

Assessing Market Leverage

Query: "What's the current leverage ratio in Bitcoin futures markets?"

Long-Term Holder Behavior

Query: "How has Bitcoin's long-term holder supply changed this month?"

Network Fee Comparison

Query: "Compare transaction fees across Bitcoin, Ethereum, and Solana over the past week"

Conclusion

The Glassnode MCP server transforms how we interact with our data, making institutional-grade analytics accessible through natural language queries. As demonstrated throughout this guide, the workflow naturally begins with discovery - exploring what metrics and assets are available - before diving into specific data retrieval. Using the metadata tools to understand parameters and requirements ensures accurate queries and optimal results.

The examples presented here showcase the server's integration with LLM chat interfaces, where users can seamlessly move from high-level exploration to granular analysis through conversational interactions. Follow-up questions flow naturally—you might start by asking about available metrics, then drill down into specific timeframes, and finally compare across multiple assets. This iterative approach makes analyses accessible to users regardless of their technical expertise.

While this guide focuses on chat-based interactions, the MCP server is equally powerful for programmatic and agentic workflows. Developers can integrate these same tools into automated systems, building sophisticated analytics pipelines that leverage Glassnode's comprehensive data coverage across 900+ metrics and 1,600+ assets.

This is currently a beta release with temporary free access for all users, providing an opportunity to explore the full capabilities of institutional-grade blockchain analytics. As the server continues to evolve, user feedback is invaluable for shaping its development.

Set up Glassnode’s MCP with your favorite tools:

• How to: Connect to Remote MCP Servers (Claude)
• How to: Connect to tools via MCP (Claude Code)
• How to: Use MCP servers (VS Code)