How do I get a Dashdoc API Key?

Log in to your Dashdoc account, navigate to **Settings > API**, and you can generate or retrieve your API Key there. Ensure your account has API access enabled.

Can the agent update transport statuses?

This integration currently focuses on listing and retrieving transport data for analysis. Status updates should be managed via the Dashdoc dashboard or driver mobile app.

Is fleet data included?

Yes, you can list your trucks, trailers, and drivers, allowing the agent to provide information on your available transport resources.

Dashdoc MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Dashdoc
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Dashdoc Specialist",
    goal="Help users interact with Dashdoc effectively",
    backstory=(
        "You are an expert at leveraging Dashdoc 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 Dashdoc "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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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 Dashdoc MCP Server

Integrate Dashdoc, the leading transport management system (TMS), directly into your AI workflow. Manage your transport orders, monitor your fleet of trucks and trailers, and track delivery addresses using natural language.

When paired with CrewAI, Dashdoc becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Dashdoc 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

Transport Management — List and retrieve detailed information for all your transport orders and their statuses.
Fleet Monitoring — Track your trucks, trailers, and drivers registered in the Dashdoc system.
Address Book — Manage delivery and pickup addresses and create new records instantly.
Partner Insights — List contacts and business partners associated with your transport operations.

The Dashdoc MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Dashdoc to CrewAI via MCP

Follow these steps to integrate the Dashdoc MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

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

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Dashdoc

Why Use CrewAI with the Dashdoc MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Dashdoc through the Model Context Protocol.

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

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

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

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

Dashdoc + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Dashdoc MCP Server delivers measurable value.

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

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

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

Compliance and audit automation: a compliance agent queries Dashdoc against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Dashdoc MCP Tools for CrewAI (10)

These 10 tools become available when you connect Dashdoc to CrewAI via MCP:

create_new_address

Persists site metadata including name, city, and postal code, returning the newly generated system ID for the address. Add a new address to your Dashdoc address book

get_my_user_info

Returns account-level metadata including user ID, role, and associated fleet/company configuration. Retrieve metadata for the current authenticated user

get_transport_details

Resolves internal IDs to human-readable names, including full site addresses, contact phone numbers, specific cargo items, and historical status logs. Get detailed information for a specific transport order

list_fleet_drivers

Returns driver profiles including internal identifiers, professional names, and link to associated vehicle units. List all drivers registered in the system

list_fleet_trailers

Returns metadata such as trailer type (e.g., refrigerated, tautliner), registration numbers, and fleet assignment status. List all trailers in your fleet

list_fleet_trucks

Includes license plates, vehicle types, maximum load capacity, and current operational status. List all trucks in your fleet

list_saved_addresses

Returns a collection of site objects with GPS coordinates, technical contact details, and site-specific instructions (e.g., gate codes, loading bay requirements). List all saved delivery and pickup addresses

list_transport_contacts

Resolves business partner identities, including legal names, tax identifiers, and primary communication channels for logistics coordination. List contacts and business partners

list_transports

Returns transport metadata including status (e.g., requested, confirmed, ongoing, done), pickup/delivery references, customer IDs, and scheduling timestamps. List all transport orders in Dashdoc

search_transports_by_reference

Matches the provided reference keyword against transport-level identifiers and customer references using case-insensitive partial matching. Search for transport orders by reference keyword

Example Prompts for Dashdoc in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Dashdoc immediately.

"List all transport orders that are 'Ongoing'."

"Show me the details for transport order 'TR123'."

"List all trucks in our fleet."

Troubleshooting Dashdoc MCP Server with CrewAI

Common issues when connecting Dashdoc to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

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

Agent not using tools

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

Timeout errors

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

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.

Dashdoc + CrewAI FAQ

Common questions about integrating Dashdoc MCP Server with CrewAI.

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.

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.

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.

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.

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.