Tingyun / 听云 MCP Server for AutoGen 10 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Tingyun / 听云 as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with McpWorkbench(
server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
transport="streamable_http",
) as workbench:
tools = await workbench.list_tools()
agent = AssistantAgent(
name="tingyun_agent",
tools=tools,
system_message=(
"You help users with Tingyun / 听云. "
"10 tools available."
),
)
print(f"Agent ready with {len(tools)} tools")
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 Tingyun / 听云 MCP Server
Empower your AI agent to orchestrate your entire digital performance stack with Tingyun (听云), the premier APM and observability platform. By connecting Tingyun to your agent, you transform complex application monitoring, incident response, and performance auditing into a natural conversation. Your agent can instantly list monitored applications, retrieve real-time performance summaries, browse active alerts, and query specific metric data without you ever needing to navigate the Tingyun console. Whether you are troubleshooting a production bottleneck or auditing system health across a distributed architecture, your agent acts as a real-time site reliability assistant, keeping your performance data accurate and your systems responsive.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Tingyun / 听云 tools. Connect 10 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.
What you can do
- Application Orchestration — List all APM applications and retrieve detailed health and performance summaries.
- Incident Control — Monitor active alerts and browse alert policies to identify and respond to performance issues.
- Infrastructure Auditing — List application instances, external service calls, and database dependencies.
- Metric Querying — Retrieve specific metric data points for applications to analyze trends and anomalies.
- User Experience Insights — Browse Real User Monitoring (RUM) browser applications to audit frontend performance.
The Tingyun / 听云 MCP Server exposes 10 tools through the Vinkius. Connect it to AutoGen 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 Tingyun / 听云 to AutoGen via MCP
Follow these steps to integrate the Tingyun / 听云 MCP Server with AutoGen.
Install AutoGen
Run pip install "autogen-ext[mcp]"
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Integrate into workflow
Use the agent in your AutoGen multi-agent orchestration
Explore tools
The workbench discovers 10 tools from Tingyun / 听云 automatically
Why Use AutoGen with the Tingyun / 听云 MCP Server
AutoGen provides unique advantages when paired with Tingyun / 听云 through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Tingyun / 听云 tools to solve complex tasks
Role-based architecture lets you assign Tingyun / 听云 tool access to specific agents. a data analyst queries while a reviewer validates
Human-in-the-loop support: agents can pause for human approval before executing sensitive Tingyun / 听云 tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Tingyun / 听云 tool responses in an isolated environment
Tingyun / 听云 + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Tingyun / 听云 MCP Server delivers measurable value.
Collaborative analysis: one agent queries Tingyun / 听云 while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Tingyun / 听云, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Tingyun / 听云 data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Tingyun / 听云 responses in a sandboxed execution environment
Tingyun / 听云 MCP Tools for AutoGen (10)
These 10 tools become available when you connect Tingyun / 听云 to AutoGen via MCP:
get_account_info
Get account metadata
get_app_summary
Get application summary
get_metrics
Query metric data
list_alert_policies
List alert policies
list_alerts
List active alerts
list_app_instances
List application instances
list_applications
List APM applications
list_browser_apps
List RUM browser applications
list_databases
List monitored databases
list_external_services
List external service calls
Example Prompts for Tingyun / 听云 in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Tingyun / 听云 immediately.
"List all applications monitored by Tingyun."
"Show me the performance summary for application ID 12345."
"Check for any critical alerts in Tingyun from today."
Troubleshooting Tingyun / 听云 MCP Server with AutoGen
Common issues when connecting Tingyun / 听云 to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Tingyun / 听云 + AutoGen FAQ
Common questions about integrating Tingyun / 听云 MCP Server with AutoGen.
How does AutoGen connect to MCP servers?
Can different agents have different MCP tool access?
Does AutoGen support human approval for tool calls?
Connect Tingyun / 听云 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 Tingyun / 听云 to AutoGen
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.