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

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Connect your CrewAI agents to Filebase (Web3 Storage) through Vinkius, pass the Edge URL in the `mcps` parameter and every Filebase (Web3 Storage) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Ask AI about this MCP Server for CrewAI

The Filebase (Web3 Storage) MCP Server for CrewAI 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

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python
from crewai import Agent, Task, Crew

agent = Agent(
    role="Filebase (Web3 Storage) Specialist",
    goal="Help users interact with Filebase (Web3 Storage) effectively",
    backstory=(
        "You are an expert at leveraging Filebase (Web3 Storage) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Filebase (Web3 Storage) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 29 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)
Filebase (Web3 Storage)
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

When paired with CrewAI, Filebase (Web3 Storage) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Filebase (Web3 Storage) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI

When CrewAI 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 CrewAI via MCP

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

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 29 tools from Filebase (Web3 Storage)

Why Use CrewAI with the Filebase (Web3 Storage) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Filebase (Web3 Storage) through the Model Context Protocol.

01

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

02

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

03

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

04

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Filebase (Web3 Storage) + CrewAI Use Cases

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

01

Automated multi-step research: a reconnaissance agent queries Filebase (Web3 Storage) for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

02

Scheduled intelligence reports: set up a crew that periodically queries Filebase (Web3 Storage), analyzes trends over time, and generates executive briefings in markdown or PDF format

03

Multi-source enrichment pipelines: chain Filebase (Web3 Storage) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

04

Compliance and audit automation: a compliance agent queries Filebase (Web3 Storage) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Filebase (Web3 Storage) in CrewAI

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

01

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

02

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

03

"What is my current storage usage on Filebase?"

Troubleshooting Filebase (Web3 Storage) MCP Server with CrewAI

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

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Filebase (Web3 Storage) + CrewAI FAQ

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

01

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.
02

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.
03

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.
04

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.
05

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.

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