Jiguang Aurora / 极光 MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Jiguang Aurora / 极光 as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Jiguang Aurora / 极光. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Jiguang Aurora / 极光?"
)
print(response)
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 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.
LlamaIndex agents combine Jiguang Aurora / 极光 tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Jiguang Aurora / 极光 MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the Jiguang Aurora / 极光 MCP Server
LlamaIndex provides unique advantages when paired with Jiguang Aurora / 极光 through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Jiguang Aurora / 极光 tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Jiguang Aurora / 极光 tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Jiguang Aurora / 极光, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Jiguang Aurora / 极光 tools were called, what data was returned, and how it influenced the final answer
Jiguang Aurora / 极光 + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Jiguang Aurora / 极光 MCP Server delivers measurable value.
Hybrid search: combine Jiguang Aurora / 极光 real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Jiguang Aurora / 极光 to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Jiguang Aurora / 极光 for fresh data
Analytical workflows: chain Jiguang Aurora / 极光 queries with LlamaIndex's data connectors to build multi-source analytical reports
Jiguang Aurora / 极光 MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Jiguang Aurora / 极光 to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Jiguang Aurora / 极光 to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpJiguang Aurora / 极光 + LlamaIndex FAQ
Common questions about integrating Jiguang Aurora / 极光 MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Jiguang Aurora / 极光 with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 Jiguang Aurora / 极光 to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.