How do I find my Jiguang App Key and Master Secret?

Log in to the [Jiguang portal](https://www.jiguang.cn/), create an application, and you will find your App Key and Master Secret in the application overview or settings section.

Can I target specific users with an alias?

Yes. Jiguang allows you to set an 'alias' for each device. You can then use the `send_push` tool with that alias in the audience payload to send targeted notifications to specific individuals.

Is it possible to track if a message was received?

Yes! Use the `get_push_report` tool with your message IDs to retrieve delivery statistics, including the count of devices that successfully received the notification.

Jiguang Aurora / 极光 MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Jiguang Aurora / 极光
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Jiguang Aurora / 极光 through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 Jiguang Aurora / 极光 "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Jiguang Aurora / 极光?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Jiguang Aurora / 极光 MCP Server

Empower your AI agent to orchestrate your push notification infrastructure with Jiguang Aurora (极光), the premier CPaaS provider in China. By connecting Jiguang to your agent, you transform complex device targeting, scheduled messaging, and multi-platform delivery into a natural conversation. Your agent can instantly send targeted push notifications, retrieve detailed device metadata by Registration ID, manage complex delivery schedules, and audit real-time message reports without you ever needing to navigate the comprehensive Jiguang portal. Whether you are automating user verification or coordinating large-scale promotional alerts, your agent acts as a real-time messaging assistant, keeping your communication flow accurate and your users informed.

Pydantic AI validates every Jiguang Aurora / 极光 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

Push Orchestration — Send customized push notifications to specific users or segments with full support for deep-linking.
Device Management — Retrieve detailed metadata for specific devices and update tags or aliases to refine your targeting.
Schedule Control — Create and manage scheduled push tasks to ensure your messages reach users at the perfect moment.
Delivery Auditing — Access real-time reports for message receipt and user engagement metrics.
Operational Insights — Monitor your account quota and API usage limits to ensure system-wide communication health.

The Jiguang Aurora / 极光 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 Jiguang Aurora / 极光 to Pydantic AI via MCP

Follow these steps to integrate the Jiguang Aurora / 极光 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 Jiguang Aurora / 极光 with type-safe schemas

Why Use Pydantic AI with the Jiguang Aurora / 极光 MCP Server

Pydantic AI provides unique advantages when paired with Jiguang Aurora / 极光 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 Jiguang Aurora / 极光 integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Jiguang Aurora / 极光 connection logic from agent behavior for testable, maintainable code

Jiguang Aurora / 极光 + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Jiguang Aurora / 极光 MCP Server delivers measurable value.

Type-safe data pipelines: query Jiguang Aurora / 极光 with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Jiguang Aurora / 极光 tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Jiguang Aurora / 极光 and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Jiguang Aurora / 极光 responses and write comprehensive agent tests

Jiguang Aurora / 极光 MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Jiguang Aurora / 极光 to Pydantic AI via MCP:

create_schedule

Create a scheduled push

delete_schedule

Delete a scheduled task

get_account_quota

Get API quota and usage

get_device_info

Get device information

get_message_status

Get detailed message status

get_push_report

Get push delivery report

get_user_report

Get user activity report

list_schedules

List scheduled push tasks

send_push

Send push notification

update_device

Update device tags and alias

Example Prompts for Jiguang Aurora / 极光 in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Jiguang Aurora / 极光 immediately.

"Send a push notification to Registration ID '1a0918c...'."

"Schedule a push task for tomorrow at 10 AM."

"Show me the user activity report for the last 7 days."

Troubleshooting Jiguang Aurora / 极光 MCP Server with Pydantic AI

Common issues when connecting Jiguang Aurora / 极光 to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Jiguang Aurora / 极光 + Pydantic AI FAQ

Common questions about integrating Jiguang Aurora / 极光 MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an 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?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Jiguang Aurora / 极光 MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.