Bring On Chain Data
to Mastra AI
Learn how to connect Glassnode (On-chain Data) to Mastra AI and start using 6 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the 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.
What you can do
- Asset Discovery — List all supported assets and blockchains using
list_assetsto identify available data points. - Metric Exploration — Query thousands of metric paths with
list_metricsand get detailed documentation on parameters viaget_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_metricto compare market trends. - Point-in-Time Data — Access immutable historical snapshots via
get_pit_metricto eliminate look-ahead bias in backtesting.
How it works
- Subscribe to this server
- Enter your Glassnode API Key
- Start querying on-chain intelligence from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Crypto Traders — monitor exchange inflows and whale movements without leaving the chat
- Data Scientists — pull clean time-series data directly into your analysis environment
- Financial Analysts — generate reports on network growth and valuation metrics instantly
Built-in capabilities (6)
Use a="*" for all assets. Get bulk metric data for multiple assets
Path should be the metric name like "addresses/active_count" or "market/price_usd_close". Get time-series data for a specific metric
Get details, allowed parameters, and description for a specific metric
Get Point-in-Time (PIT) metric data
List all supported assets on Glassnode
Can be filtered by asset, interval, etc. List all available metric paths on Glassnode
Why Mastra AI?
Mastra's agent abstraction provides a clean separation between LLM logic and Glassnode (On-chain Data) tool infrastructure. Connect 6 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Glassnode (On-chain Data) without touching business code
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Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
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TypeScript-native: full type inference for every Glassnode (On-chain Data) tool response with IDE autocomplete and compile-time checks
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One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
Glassnode (On-chain Data) in Mastra AI
Glassnode (On-chain Data) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Glassnode (On-chain Data) to Mastra AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Glassnode (On-chain Data) in Mastra AI
The Glassnode (On-chain Data) MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 6 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Mastra AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Glassnode (On-chain Data) for Mastra AI
Every tool call from Mastra AI to the Glassnode (On-chain Data) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I find the exact path for a specific metric like 'Active Addresses'?
Use the list_metrics tool with the asset symbol (e.g., 'BTC') to see all available paths, or use get_metric_details with a known path to see its full documentation and allowed parameters.
Can I fetch data for multiple coins at once?
Yes, use the get_bulk_metric tool. You can specify a specific asset or use a wildcard * to get data for all supported assets for a specific metric path in a single response.
What is the difference between standard metrics and Point-in-Time (PIT) metrics?
Standard get_metric returns the most accurate current data (which may include revisions). get_pit_metric provides an immutable view of data as it was known at a specific moment, which is essential for backtesting to avoid look-ahead bias.
How does Mastra AI connect to MCP servers?
Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
Can Mastra agents use tools from multiple servers?
Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
Does Mastra support workflow orchestration?
Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.
createMCPClient not exported
Install: npm install @mastra/mcp
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