How to Use the FutureVault MCP in CrewAI

Q: How do I connect my CrewAI agents to FutureVault?

You can pass your Vinkius endpoint URL directly into the mcps parameter of your CrewAI agents. This registers tools like listdigitalvaults for the entire crew to use.

Deploy a collaborative crew of specialized agents in CrewAI using this MCP Server to manage and audit your FutureVault documents autonomously.

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Connect FutureVault MCP to CrewAI

Create your Vinkius account to connect FutureVault to CrewAI 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 FutureVault with CrewAI

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Run multi-agent document audits in CrewAI

`search_vault_content` enables your research agent to find specific tax forms and legal agreements across all digital vaults. The agent searches for keywords and flags documents that require a closer look by your compliance agent. Once flagged, the compliance agent uses `get_document_metadata` to verify the document's properties. CrewAI's shared memory allows these specialized agents to hand off document IDs directly, completing audits without human intervention.

Map folder structures with this MCP Server

`list_vault_folders` allows your mapping agent to extract the complete directory layout of any target vault. The agent traverses the folder hierarchy, identifying nested structures and empty directories. The mapping agent then passes this hierarchy to an optimization agent. Using CrewAI's hierarchical process, the team analyzes the folder layout and recommends cleanups for messy directory paths.

Verify member access roles using CrewAI

`get_my_identity` retrieves the profile details of the active user session, ensuring your agent team knows exactly who is running the commands. This is the first check the crew executes before performing any data operations. If the identity is valid, a security agent runs `list_vault_members` to cross-reference the user's access level against the vault's member list. CrewAI ensures this multi-step verification happens in sequence before any sensitive data is accessed.

Setup guide

Set up FutureVault MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke FutureVault tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="FutureVault Analyst",
    goal="Access and analyze FutureVault data via MCP.",
    backstory="Expert analyst with direct FutureVault access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent FutureVault transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="FutureVault Analyst",
        goal="Access and analyze FutureVault data via MCP.",
        backstory="Expert analyst with direct FutureVault access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent FutureVault transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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

You can pass your Vinkius endpoint URL directly into the `mcps` parameter of your CrewAI agents. This registers tools like `list_digital_vaults` for the entire crew to use.

Yes, CrewAI supports shared tool access. Your research agent can run `search_vault_content` while your compliance agent simultaneously runs `get_document_metadata` on the results.

CrewAI assigns the search task to a specialized agent equipped with the `search_vault_content` tool. The agent executes the search, filters the results, and passes the clean data to the next agent in the pipeline.

No, the MCP Server handles the tool definitions automatically. CrewAI reads the schema from the Vinkius endpoint, meaning tools like `get_vault_details` are ready to use out of the box.

The integration uses a secure, single-endpoint token managed by Vinkius. Your CrewAI agents only access document metadata like file names and sizes through tools like `get_document_metadata`, keeping the actual contents of your client tax forms completely isolated from the LLM context.

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