Adikteev MCP Server for Google ADK 5 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Adikteev as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
StreamableHTTPConnectionParams,
)
# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
)
)
agent = Agent(
model="gemini-2.5-pro",
name="adikteev_agent",
instruction=(
"You help users interact with Adikteev "
"using 5 available tools."
),
tools=[mcp_tools],
)
* 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.
Google ADK natively supports Adikteev as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 5 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
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 Google ADK 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 Google ADK via MCP
Follow these steps to integrate the Adikteev MCP Server with Google ADK.
Install Google ADK
Run pip install google-adk
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Create the agent
Save the code above and integrate into your ADK workflow
Explore tools
The agent will discover 5 tools from Adikteev via MCP
Why Use Google ADK with the Adikteev MCP Server
Google ADK provides unique advantages when paired with Adikteev through the Model Context Protocol.
Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Adikteev
Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
Seamless integration with Google Cloud services means you can combine Adikteev tools with BigQuery, Vertex AI, and Cloud Functions
Adikteev + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Adikteev MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Adikteev and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Adikteev tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Adikteev regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Adikteev
Adikteev MCP Tools for Google ADK (5)
These 5 tools become available when you connect Adikteev to Google ADK 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 Google ADK
Ready-to-use prompts you can give your Google ADK 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 Google ADK
Common issues when connecting Adikteev to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkAdikteev + Google ADK FAQ
Common questions about integrating Adikteev MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
Connect Adikteev with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 Adikteev to Google ADK
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.