Adikteev MCP Server for AutoGen 5 tools — connect in under 2 minutes
Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Adikteev 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="adikteev_agent",
tools=tools,
system_message=(
"You help users with Adikteev. "
"5 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 Adikteev MCP Server
Connect your Adikteev account to your AI agent to unlock professional app retargeting and user retention insights. From managing custom audience segments to monitoring campaign performance and retrieving churn probability scores, your agent handles your mobile growth ecosystem through natural conversation.
AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Adikteev tools. Connect 5 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
- Audience Orchestration — List, create, and manage audience segments for targeted app retargeting campaigns
- Performance Reporting — Retrieve detailed campaign performance data to monitor ROI and engagement metrics
- Churn Prediction — Access churn probability scores to identify at-risk app users before they leave your ecosystem
- Company Insights — List companies and retrieve technical metadata required for audience management
- Growth Monitoring — Quickly audit your retargeting efforts and identify high-value user segments directly from chat
The Adikteev MCP Server exposes 5 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 Adikteev to AutoGen via MCP
Follow these steps to integrate the Adikteev 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 5 tools from Adikteev automatically
Why Use AutoGen with the Adikteev MCP Server
AutoGen provides unique advantages when paired with Adikteev through the Model Context Protocol.
Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Adikteev tools to solve complex tasks
Role-based architecture lets you assign Adikteev 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 Adikteev tool calls
Code execution sandbox: AutoGen agents can write and run code that processes Adikteev tool responses in an isolated environment
Adikteev + AutoGen Use Cases
Practical scenarios where AutoGen combined with the Adikteev MCP Server delivers measurable value.
Collaborative analysis: one agent queries Adikteev while another validates results and a third generates the final report
Automated review pipelines: a researcher agent fetches data from Adikteev, a critic agent evaluates quality, and a writer produces the output
Interactive planning: agents negotiate task allocation using Adikteev data to make informed decisions about resource distribution
Code generation with live data: an AutoGen coder agent writes scripts that process Adikteev responses in a sandboxed execution environment
Adikteev MCP Tools for AutoGen (5)
These 5 tools become available when you connect Adikteev to AutoGen via MCP:
create_segment
Create an audience segment
get_churn_scores
Retrieve user churn scores
get_reporting
Get campaign performance data
list_companies
Retrieve your company ID
list_segments
List audience segments
Example Prompts for Adikteev in AutoGen
Ready-to-use prompts you can give your AutoGen agent to start working with Adikteev immediately.
"List all audience segments for my company."
"Retrieve the churn scores for my app with bundle 'com.example.app'."
"Show me the performance of my retargeting campaigns."
Troubleshooting Adikteev MCP Server with AutoGen
Common issues when connecting Adikteev to AutoGen through the Vinkius, and how to resolve them.
McpWorkbench not found
pip install "autogen-ext[mcp]"Adikteev + AutoGen FAQ
Common questions about integrating Adikteev 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 Adikteev with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
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 Adikteev to AutoGen
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.