Dashdoc MCP Server for Pydantic AI 10 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Dashdoc through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Dashdoc "
"(10 tools)."
),
)
result = await agent.run(
"What tools are available in Dashdoc?"
)
print(result.data)
asyncio.run(main())
* 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.
Pydantic AI validates every Dashdoc tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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
- 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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the Dashdoc MCP Server with Pydantic AI.
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 10 tools from Dashdoc with type-safe schemas
Why Use Pydantic AI with the Dashdoc MCP Server
Pydantic AI provides unique advantages when paired with Dashdoc 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 Dashdoc integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Dashdoc connection logic from agent behavior for testable, maintainable code
Dashdoc + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Dashdoc MCP Server delivers measurable value.
Type-safe data pipelines: query Dashdoc with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Dashdoc tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Dashdoc and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Dashdoc responses and write comprehensive agent tests
Dashdoc MCP Tools for Pydantic AI (10)
These 10 tools become available when you connect Dashdoc to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Dashdoc to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiDashdoc + Pydantic AI FAQ
Common questions about integrating Dashdoc MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
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?
Can I switch LLM providers without changing MCP code?
Connect Dashdoc with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Dashdoc to Pydantic AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.