How to Use the AfterShip MCP in CrewAI
Deploy specialized CrewAI agent teams to automate your shipping operations and track packages with AfterShip.
Works with every AI agent you already use
…and any MCP-compatible client
Connect AfterShip MCP to CrewAI
Create your Vinkius account to connect AfterShip 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.
Multi-agent shipping operations in CrewAI
The `list_trackings` and `get_tracking` tools provide your agent teams with complete visibility over active deliveries. A support agent can check delivery statuses while a notification agent alerts customers of delayed packages. By dividing these duties among specialized agents, CrewAI avoids overloading a single agent with too many tasks. Your logistics crew coordinates tracking checks in the background, keeping your team updated.
Collaborative courier lookup and setup
The `detect_courier` and `create_tracking` tools are used by your intake agents to register new shipments automatically. When a customer submits a tracking code, your intake agent identifies the carrier and passes the data to a logistics agent to create the record. Using this MCP Server ensures that your agents don't have to guess carrier names. They pass the raw tracking number to the detection tool, verify the result, and register the package instantly.
Automated shipment maintenance and recovery
The `retrack_tracking` and `update_tracking` tools let your agents maintain the health of your tracking database. When an agent detects a stalled or expired shipment, it triggers a retrack request to fetch fresh checkpoint updates. Because CrewAI agents share memory, they can note which tracking numbers repeatedly fail. The agent can update customer details or flag the record for manual review without starting from scratch.
Set up AfterShip MCP in CrewAI
Prerequisites
- Python 3.10+ installed
-
crewaipackage (pip install crewai) - Active Vinkius subscription with a valid endpoint token
- 1
Install CrewAI
Run
pip install crewaito install the framework. MCP support is built-in via themcpsparameter. - 2
Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the
mcpslist. 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
Crewwith your agent and tasks. Callcrew.kickoff()— the agent will automatically invoke AfterShip tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="AfterShip Analyst",
goal="Access and analyze AfterShip data via MCP.",
backstory="Expert analyst with direct AfterShip access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent AfterShip transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Prerequisites
- Python 3.10+ installed
-
crewai+crewai-toolspackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
pip install crewai crewai-tools. TheMCPServerAdapterhandles lifecycle management and tool conversion. - 2
Connect with MCPServerAdapter
Use
MCPServerAdapteras a context manager withSseServerParameterspointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle. - 3
Assign tools and run
Pass the returned
mcp_toolsto your agent'stoolsparameter. The adapter converts MCP tools to nativeBaseToolobjects compatible with all CrewAI agents.
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="AfterShip Analyst",
goal="Access and analyze AfterShip data via MCP.",
backstory="Expert analyst with direct AfterShip access.",
tools=mcp_tools,
)
task = Task(
description="List recent AfterShip transactions",
agent=agent,
expected_output="A summary of recent activity",
)
crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AfterShip. 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 AfterShip MCP in CrewAI
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