Arize AI MCP Server for Google ADK 10 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Arize AI 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="arize_ai_agent",
instruction=(
"You help users interact with Arize AI "
"using 10 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 Arize AI MCP Server
Connect your Arize AI observability platform to any AI agent and take full control of your Machine Learning and LLM telemetry workflows through natural conversation.
Google ADK natively supports Arize AI as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 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
- Model Monitoring & Metrics — List all tracked ML models, extract deep configuration schemas, and fetch real-time metrics (performance, data quality, and prediction drift)
- Evaluation & Alignment — Launch and list automated LLM evaluation runs (e.g., Toxicity, Hallucination, PII filtering) against static datasets and ground truth baselines
- Telemetry Ingestion — Push programmatic raw logs, predictions, and inferences straight into Arize for immediate visualization and tracking
- Space & Environment Management — Browse organizational spaces and segregated deployment environments (Production, Training, Verification)
The Arize AI MCP Server exposes 10 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 Arize AI to Google ADK via MCP
Follow these steps to integrate the Arize AI 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 10 tools from Arize AI via MCP
Why Use Google ADK with the Arize AI MCP Server
Google ADK provides unique advantages when paired with Arize AI 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 Arize AI
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 Arize AI tools with BigQuery, Vertex AI, and Cloud Functions
Arize AI + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Arize AI MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Arize AI and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Arize AI tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Arize AI regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Arize AI
Arize AI MCP Tools for Google ADK (10)
These 10 tools become available when you connect Arize AI to Google ADK via MCP:
get_dataset
Get a specific evaluation dataset
get_metrics
Fetch observability metrics for an ML model
get_model
It defines the inputs, outputs, and features. Get details and metadata for a specific tracked model
ingest_log
payload_json must contain valid Arize payload structures. Ingest raw telemetry logs into Arize
list_datasets
List static evaluation datasets
list_environments
g., Production, Training, Verification) used to segregate model inferences and baseline datasets. List configured environments within Arize
list_evals
g., Toxicity, Hallucination, PII filtering). List automated evaluation runs
list_models
List tracked ML models or LLMs
list_spaces
Spaces separate different models and telemetry datasets. List accessible workspaces within the Arize platform
run_eval
Trigger a custom LLM evaluation run
Example Prompts for Arize AI in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Arize AI immediately.
"List all active Machine Learning models monitored in my workspace."
"Get the evaluation baseline datasets available for our LLM checks."
"Push these 3 mocked prompt responses as telemetry logs to the 'OpenAI-Customer-Service-Bot' model."
Troubleshooting Arize AI MCP Server with Google ADK
Common issues when connecting Arize AI to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkArize AI + Google ADK FAQ
Common questions about integrating Arize AI 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 Arize AI 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 Arize AI to Google ADK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.