How to Use the Filebase (Web3 Storage) MCP in Mastra AI

Q: How to monitor Filebase (Web3 Storage) usage in Mastra AI?

Use platformgetusage within a scheduled agent task. You can set thresholds that trigger alerts or cleanup actions if your storage gets too full.

Build reliable storage workflows in Mastra AI. Manage IPFS pins and gateways with automated retries and clear branching logic.

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Connect Filebase (Web3 Storage) MCP to Mastra AI

Create your Vinkius account to connect Filebase (Web3 Storage) 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 Filebase (Web3 Storage) with Mastra AI

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Conditional storage workflows

Create logic branches that react to storage states. If `platform_get_usage` returns a high volume, trigger a cleanup using `psa_remove_pin` or `rpc_pin_rm`. This keeps your infrastructure lean. You define the rules, and the agent executes them based on the actual usage data it fetches.

Resilient pinning for Mastra AI

Use `psa_replace_pin` to manage content updates across your decentralized stack. The framework handles the execution, ensuring your pins remain active even if one node goes down. It moves the heavy lifting to the background. You focus on the workflow, and the server ensures the data stays pinned on the network.

Gateway orchestration in Mastra AI

Manage your dedicated gateways programmatically with `platform_list_gateways` and `platform_create_gateway`. Your agent can provision new access points as your project scales. It automates the boring infrastructure tasks. You get a clean, observable pipeline that manages your storage endpoints without human oversight.

Setup guide

Set up Filebase (Web3 Storage) 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 Filebase (Web3 Storage) 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: "filebase-web3-storage-mcp-client",
  servers: {
    "filebase-web3-storage-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Filebase (Web3 Storage) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Filebase (Web3 Storage) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Filebase (Web3 Storage) transactions"
);
console.log(result.text);

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Common questions about Filebase (Web3 Storage) MCP in Mastra AI

Include the server in your Mastra agent configuration. Once connected, your workflows can call any of the 29 available tools to manage your IPFS content.

Absolutely. You can build a workflow that watches for new uploads and automatically triggers `psa_add_pin` to ensure durability.

Use `platform_get_usage` within a scheduled agent task. You can set thresholds that trigger alerts or cleanup actions if your storage gets too full.

The MCP Server operates as a private bridge. Only your authorized agents can trigger tools to access or modify your storage buckets.

The server manages the API requests for file operations. It handles the CID pinning process efficiently, allowing your agents to work with large datasets.

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