How to Use the Fireblocks MCP in Mastra AI

Q: Does Mastra AI support human approval for Fireblocks transactions?

Yes, use the requireToolApproval setting on your agent. This forces a human to sign off on createtransaction before the MCP server sends it.

Build resilient treasury workflows in Mastra AI. Automated retries and conditional logic for your Fireblocks assets.

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Connect Fireblocks MCP to Mastra AI

Create your Vinkius account to connect Fireblocks to Mastra AI 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 Fireblocks with Mastra AI

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Automated asset movement in Mastra AI

Chain `create_transaction` with `list_transactions` to build autonomous fund management. Mastra AI handles the logic, ensuring your treasury rules execute reliably. Configure retries for `estimate_fee` calls to handle network congestion. If a fee spike occurs, your agent adjusts automatically.

Vault management inside Mastra AI agents

Deploy `create_vault_account` as part of your agent setup routine. It creates a fresh container for each client or project automatically. Use `update_vault_account` to organize your infrastructure as you scale. Your agent maintains the naming convention based on your workflow state.

Compliance enforcement in Mastra AI

Run `validate_travel_rule` as a mandatory step in your agent's transaction pipeline. If the check fails, the workflow aborts before the transaction hits the blockchain. Pull `get_screening_transaction` results to verify compliance status. You get clear signals to halt or proceed based on the data.

Setup guide

Set up Fireblocks MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Fireblocks tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "fireblocks-mcp-client",
  servers: {
    "fireblocks-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Fireblocks Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Fireblocks tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Fireblocks transactions"
);
console.log(result.text);

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fireblocks. 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 Fireblocks MCP in Mastra AI

Yes, use the `requireToolApproval` setting on your agent. This forces a human to sign off on `create_transaction` before the MCP server sends it.

Definitely. Mastra AI's workflow engine manages the state. If `create_transaction` fails, you can trigger a fallback or retry with different parameters.

The server only touches the data you request via tools. Your vault credentials remain isolated in your environment, and you define the strict tool access list.

Your agent catches the error. You can define a backoff strategy in your workflow to wait and retry the call once the limit resets.

Pass a tool filter to the MCP client configuration. This limits your agent to only the specific tools it needs for its assigned role.

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