How to Use the Jiguang Aurora / 极光 MCP in CrewAI
Autonomous messaging crews. Jiguang Aurora / 极光 powers your CrewAI notification operations.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Jiguang Aurora / 极光 MCP to CrewAI
Create your Vinkius account to connect Jiguang Aurora / 极光 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.
Specialized notification crews for CrewAI
Assign a 'Messenger' agent to handle your outbound traffic. Using `send_push`, this agent can act on behalf of your team to keep users engaged. It works within the shared memory of your crew. Other agents can query the results to see if the message actually landed.
Audit notification health with CrewAI
Deploy a 'Monitor' agent to watch your delivery stats. It uses `get_push_report` to check for anomalies in your messaging volume. If the agent spots a drop in delivery, it can escalate to your human team. You get automated oversight of your entire notification stack.
Update user segments on the fly
Maintain your audience lists with targeted updates. Agents use `update_device` to refine tags based on behavior observed during the session. This keeps your segments accurate. You aren't sending broadcasts to inactive devices; you're hitting the right audience every time.
Set up Jiguang Aurora / 极光 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 Jiguang Aurora / 极光 tools as needed.
from crewai import Agent, Task, Crew
agent = Agent(
role="Jiguang Aurora / 极光 Analyst",
goal="Access and analyze Jiguang Aurora / 极光 data via MCP.",
backstory="Expert analyst with direct Jiguang Aurora / 极光 access.",
mcps=[
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
],
)
task = Task(
description="List recent Jiguang Aurora / 极光 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="Jiguang Aurora / 极光 Analyst",
goal="Access and analyze Jiguang Aurora / 极光 data via MCP.",
backstory="Expert analyst with direct Jiguang Aurora / 极光 access.",
tools=mcp_tools,
)
task = Task(
description="List recent Jiguang Aurora / 极光 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 Jiguang Aurora / 极光. 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.
Why Choose Vinkius
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Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
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Common questions about Jiguang Aurora / 极光 MCP in CrewAI
Use it with your favorite AI tools
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