How to Use the Dashdoc MCP in CrewAI

Q: How to filter Dashdoc tools in CrewAI?

You use the toolfilter parameter when setting up your agents. This allows you to restrict certain agents to only read data while others handle createnewaddress tasks.

Deploy a CrewAI team to autonomously monitor and act on your Dashdoc transport operations.

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Connect Dashdoc MCP to CrewAI

Create your Vinkius account to connect Dashdoc 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 Dashdoc with CrewAI

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Deploy specialized agents for Dashdoc operations

Assign specific roles to your crew members for logistics management. One agent runs `list_transports` to find delays, while another uses `get_transport_details` to investigate the specific cargo and site requirements. They collaborate to keep your schedule clean. You focus on the high-level strategy while the crew handles the individual order monitoring.

Coordinate fleet resources with CrewAI

Let your crew manage your drivers and vehicles using `list_fleet_drivers` and `list_fleet_trucks`. The team verifies if your fleet assignments match current transport needs without you writing a single line of procedural code. It works autonomously. If the fleet agent detects a shortage of trailers, it alerts the moderator agent to escalate the issue.

Manage business contacts via CrewAI

Your agents maintain your partner directory with `list_transport_contacts`. They resolve legal names and tax identifiers for every transport order in the system. This keeps your records accurate. The crew ensures every piece of metadata stays current as your logistics operations scale.

Setup guide

Set up Dashdoc 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 Dashdoc tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Dashdoc 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="Dashdoc Analyst",
        goal="Access and analyze Dashdoc data via MCP.",
        backstory="Expert analyst with direct Dashdoc access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Dashdoc 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 Dashdoc. 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 Dashdoc MCP in CrewAI

You use the tool_filter parameter when setting up your agents. This allows you to restrict certain agents to only read data while others handle `create_new_address` tasks.

Yes, CrewAI uses shared memory between agents. Once one agent retrieves transport metadata, the rest of the crew has access to that information for their respective tasks.

Your logistics information travels through a secure, ephemeral sandbox. We ensure your transport references and internal IDs are never exposed to other users or external systems.

You pass the Vinkius endpoint URL directly into the mcps list for your agents. The server then handles the handshake and exposes the tools for your crew.

We keep your transport logs and contact information siloed. Access is restricted to your endpoint token, and we do not persist your shipment details after the agent session finishes.

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