Filebase (Web3 Storage) MCP Server for Pydantic AIGive Pydantic AI instant access to 29 tools to Platform Create Gateway, Platform Create Name, Platform Delete Gateway, and more

Name: Filebase (Web3 Storage)
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Filebase (Web3 Storage) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Filebase (Web3 Storage) MCP Server for Pydantic AI is a standout in the Developer Tools category — giving your AI agent 29 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Filebase (Web3 Storage) "
            "(29 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Filebase (Web3 Storage)?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

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* 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

About Filebase (Web3 Storage) MCP Server

Connect your Filebase account to any AI agent and take full control of your decentralized Web3 storage workflows through natural conversation.

Pydantic AI validates every Filebase (Web3 Storage) tool response against typed schemas, catching data inconsistencies at build time. Connect 29 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

IPFS Operations — Add text files, fetch content by CID, and manage raw blocks directly on the IPFS network using the RPC API.
Pinning Management — Use the Pinning Service API (PSA) or RPC to pin, list, and remove content identifiers (CIDs) for persistent storage.
IPNS & Keys — Generate keypairs, publish CIDs to IPNS, and resolve names to IPFS paths for mutable decentralized websites.
Usage & Infrastructure — Monitor storage usage, manage dedicated gateways, and track bucket metrics across the platform.

The Filebase (Web3 Storage) MCP Server exposes 29 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 29 Filebase (Web3 Storage) tools available for Pydantic AI

When Pydantic AI connects to Filebase (Web3 Storage) through Vinkius, your AI agent gets direct access to every tool listed below — spanning ipfs, web3, decentralized-storage, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

platform

Platform create gateway on Filebase (Web3 Storage)

Create a new dedicated gateway

platform

Platform create name on Filebase (Web3 Storage)

Create a new IPNS name

platform

Platform delete gateway on Filebase (Web3 Storage)

Delete a dedicated gateway

platform

Platform delete name on Filebase (Web3 Storage)

Delete an IPNS name

platform

Platform get bucket usage on Filebase (Web3 Storage)

Get storage usage for a specific bucket

platform

Platform get gateway on Filebase (Web3 Storage)

Get details of a specific dedicated gateway

platform

Platform get gateway usage on Filebase (Web3 Storage)

Get bandwidth usage for a dedicated gateway

platform

Platform get name on Filebase (Web3 Storage)

Get details of a specific IPNS name

platform

Platform get usage on Filebase (Web3 Storage)

Get total storage and bandwidth usage

platform

Platform list gateways on Filebase (Web3 Storage)

List all dedicated gateways

platform

Platform list names on Filebase (Web3 Storage)

List all IPNS names

platform

Platform update gateway on Filebase (Web3 Storage)

Update a dedicated gateway

platform

Platform update name on Filebase (Web3 Storage)

Update an IPNS name to point to a new CID

psa

Psa add pin on Filebase (Web3 Storage)

Add a pin using the Pinning Service API

psa

Psa get pin on Filebase (Web3 Storage)

Get pin status by request ID

psa

Psa list pins on Filebase (Web3 Storage)

List pins using the Pinning Service API

psa

Psa remove pin on Filebase (Web3 Storage)

Remove a pin by request ID

psa

Psa replace pin on Filebase (Web3 Storage)

Replace an existing pin

rpc

Rpc add on Filebase (Web3 Storage)

Add a text file to IPFS

rpc

Rpc block get on Filebase (Web3 Storage)

Retrieve a raw block by CID

rpc

Rpc cat on Filebase (Web3 Storage)

Fetch contents of a file by CID

rpc

Rpc key gen on Filebase (Web3 Storage)

Create a new keypair

rpc

Rpc key list on Filebase (Web3 Storage)

List all keys in the keychain

rpc

Rpc name publish on Filebase (Web3 Storage)

Publish a CID to IPNS

rpc

Rpc name resolve on Filebase (Web3 Storage)

Resolve an IPNS name to an IPFS path

rpc

Rpc pin add on Filebase (Web3 Storage)

Pin a CID to persistent storage

rpc

Rpc pin ls on Filebase (Web3 Storage)

List all pinned objects via RPC

rpc

Rpc pin rm on Filebase (Web3 Storage)

Unpin a CID via RPC

rpc

Rpc version on Filebase (Web3 Storage)

Get the version of the IPFS daemon

Connect Filebase (Web3 Storage) to Pydantic AI via MCP

Follow these steps to wire Filebase (Web3 Storage) into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 29 tools from Filebase (Web3 Storage) with type-safe schemas

Why Use Pydantic AI with the Filebase (Web3 Storage) MCP Server

Pydantic AI provides unique advantages when paired with Filebase (Web3 Storage) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Filebase (Web3 Storage) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Filebase (Web3 Storage) connection logic from agent behavior for testable, maintainable code

Filebase (Web3 Storage) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Filebase (Web3 Storage) MCP Server delivers measurable value.

Type-safe data pipelines: query Filebase (Web3 Storage) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Filebase (Web3 Storage) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Filebase (Web3 Storage) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Filebase (Web3 Storage) responses and write comprehensive agent tests

Example Prompts for Filebase (Web3 Storage) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Filebase (Web3 Storage) immediately.

"Upload the text 'Hello from Filebase MCP' to IPFS."

"Show me a list of all my pinned objects."

"What is my current storage usage on Filebase?"

Troubleshooting Filebase (Web3 Storage) MCP Server with Pydantic AI

Common issues when connecting Filebase (Web3 Storage) to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Filebase (Web3 Storage) + Pydantic AI FAQ

Common questions about integrating Filebase (Web3 Storage) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Filebase (Web3 Storage) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.