Zingtree MCP Server for AutoGen 8 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Zingtree as an MCP tool provider through the 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="zingtree_agent",
tools=tools,
system_message=(
"You help users with Zingtree. "
"8 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 Zingtree MCP Server
Connect your Zingtree account to any AI agent to streamline your interactive workflows and decision tree management. This MCP server enables your agent to interact with trees, nodes, and detailed user session data directly from natural language.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Zingtree tools. Connect 8 tools through the 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
- Tree Oversight — List all interactive trees in your organization and retrieve their hierarchical structures
- Content Search — Search for specific text, keywords, or labels across all your nodes and workflows
- Session Analysis — Access detailed path data, browser info, and interaction history for any user session
- Form Data Extraction — Retrieve all values and answers entered by users during their tree interactions
- Historical Tracking — List sessions for specific trees within any date range to monitor performance and usage
The Zingtree MCP Server exposes 8 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 Zingtree to AutoGen via MCP
Follow these steps to integrate the Zingtree 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 8 tools from Zingtree automatically
Why Use AutoGen with the Zingtree MCP Server
AutoGen provides unique advantages when paired with Zingtree through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Zingtree tools to solve complex tasks
Role-based architecture lets you assign Zingtree 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 Zingtree tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Zingtree tool responses in an isolated environment
Zingtree + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Zingtree MCP Server delivers measurable value.
Collaborative analysis: one agent queries Zingtree while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Zingtree, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Zingtree data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Zingtree responses in a sandboxed execution environment
Zingtree MCP Tools for AutoGen (8)
These 8 tools become available when you connect Zingtree to AutoGen via MCP:
get_clean_session_path
Get a clean linear path for a user session
get_session_details
Get detailed data for a specific user session
get_session_form_data
Get all form data entered during a session
get_tree_structure
Get the full structure of a specific tree
list_tree_sessions
List sessions for a tree within a date range
list_tree_variables
List all variables used in a tree
list_trees
List all interactive trees in the organization
search_all_trees
Search for text within all decision trees
Example Prompts for Zingtree in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Zingtree immediately.
"List all decision trees in my Zingtree account."
"Show me the structure for tree ID '12345'."
"Get the form data for session ID 'XYZ-987-ABC'."
Troubleshooting Zingtree MCP Server with AutoGen
Common issues when connecting Zingtree to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Zingtree + AutoGen FAQ
Common questions about integrating Zingtree 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 Zingtree 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.
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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 Zingtree to AutoGen
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.