Google ADK: 30+ Integrations for AI Agents

Google’s Agent Development Kit (ADK) is an orchestration framework that connects AI agents to over 30 third-party platforms via a uniform McpToolset configuration. For enterprises, this turns the technical bottleneck of tool integration into a commodity, shifting the operational focus to critical governance, observability, and permission controls.

An agent that "thinks" is interesting. An agent that opens a PR on GitHub, fires a payment on Stripe, writes semantic memory to Qdrant and sends an email via Mailgun — all in a single orchestrated flow — is operationally useful. On February 27, 2026, Google announced exactly that: the expansion of the Agent Development Kit (ADK) with more than 30 native integrations from leading partners.

  <hr />

  <h2>What Google announced — without romanticizing</h2>
  <p>The <a href="https://developers.googleblog.com/supercharge-your-ai-agents-adk-integrations-ecosystem/" target="_blank" rel="noopener">official Google Developers blog</a> (Feb 27, 2026) describes the ADK expansion as an ecosystem of third-party integrations organized into eight functional categories. The premise is straightforward: the framework already provided orchestration primitives; it now delivers ready-made connectors for the real world.</p>

  <p>The integration architecture is uniform: you configure a <code>McpToolset</code> pointing to the partner's MCP endpoint (or use the ADK's native <code>plugin</code>), pass scoped credentials and the agent gains access to that system's tools. The core agent — model, instructions, memory — doesn't change.</p>

  <div class="blog-table-container">
    <table class="blog-table">
      <thead>
        <tr>
          <th>Category</th>
          <th>Available partners</th>
          <th>Example agent action</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <td><strong>Code & Dev</strong></td>
          <td>Daytona, GitHub, GitLab, Postman, Restate</td>
          <td>Open PR, run tests in isolated sandbox, inspect CI/CD pipeline</td>
        </tr>
        <tr>
          <td><strong>Project Management</strong></td>
          <td>Asana, Atlassian, Linear, Notion</td>
          <td>Create issue, update sprint, search documentation in Confluence</td>
        </tr>
        <tr>
          <td><strong>Databases & Vector</strong></td>
          <td>Chroma, MongoDB, Pinecone</td>
          <td>Semantic search, collection query, result reranking</td>
        </tr>
        <tr>
          <td><strong>Persistent Memory</strong></td>
          <td>GoodMem, Qdrant</td>
          <td>Save context between sessions, retrieve multimodal memory</td>
        </tr>
        <tr>
          <td><strong>Observability</strong></td>
          <td>AgentOps, Arize AX, MLflow, W&B Weave, Phoenix</td>
          <td>Session replay, tool-use tracing, LLM evaluation in production</td>
        </tr>
        <tr>
          <td><strong>Connectors</strong></td>
          <td>n8n, StackOne</td>
          <td>Trigger workflow, connect to 200+ SaaS via unified gateway</td>
        </tr>
        <tr>
          <td><strong>Payments</strong></td>
          <td>PayPal, Stripe</td>
          <td>Issue invoice, process subscription, query history</td>
        </tr>
        <tr>
          <td><strong>Voice & Audio</strong></td>
          <td>Cartesia, ElevenLabs</td>
          <td>Generate speech, clone voice, transcribe audio</td>
        </tr>
        <tr>
          <td><strong>Email & Messaging</strong></td>
          <td>AgentMail, Mailgun</td>
          <td>Manage dedicated agent inbox, send and track emails</td>
        </tr>
        <tr>
          <td><strong>AI & Datasets</strong></td>
          <td>Hugging Face</td>
          <td>Access models, datasets and papers; run Gradio apps</td>
        </tr>
      </tbody>
    </table>
  </div>

  <p>Beyond third-party integrations, the ADK already includes native connectors to Google Cloud services: BigQuery, Spanner, Pub/Sub and others — relevant for those operating within the GCP ecosystem.</p>

  <hr />

  <h2>What this means in practice — the section that matters</h2>

  <h3>Before vs. After the ADK ecosystem</h3>
  <div class="blog-table-container">
    <table class="blog-table">
      <thead>
        <tr>
          <th>Scenario</th>
          <th>Before (manual integration)</th>
          <th>Now (ADK + McpToolset)</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <td>Agent opens PR on GitHub</td>
          <td>GitHub SDK + custom wrapper + manual auth</td>
          <td><code>McpToolset</code> with scoped token, 10 lines of config</td>
        </tr>
        <tr>
          <td>Agent saves memory between sessions</td>
          <td>Own vector database + embedding logic + retrieval</td>
          <td>Qdrant or GoodMem plugin with automatic persistence</td>
        </tr>
        <tr>
          <td>Agent triggers payment</td>
          <td>Manual Stripe integration + validation + audit</td>
          <td>Stripe plugin — but <strong>requires human approval guardrail</strong></td>
        </tr>
        <tr>
          <td>Observe what the agent did</td>
          <td>Ad-hoc logs, no tool-use traceability</td>
          <td>AgentOps / Phoenix / MLflow with native ADK tracing</td>
        </tr>
      </tbody>
    </table>
  </div>

  <h3>4-step adoption pipeline (workshop-tested)</h3>
  <ol>
    <li><strong>Map the target workflow</strong> — identify which systems the agent needs to touch and in what order. Don't connect everything at once.</li>
    <li><strong>Start with read integrations</strong> — GitHub read-only, Notion search, Confluence query. Validate the agent's reasoning before enabling writes.</li>
    <li><strong>Add observability before production</strong> — install AgentOps or Phoenix from the start. Without tracing, you're flying blind.</li>
    <li><strong>Enable writes/payments with human approval</strong> — use <code>human_in_the_loop</code> for irreversible actions (merge, payment, mass email send).</li>
  </ol>

  <hr />

  <h2>Risks and frictions the announcement doesn't mention</h2>

  <p>The ADK ecosystem solves the connection problem. But the <strong>governance</strong> problem is yours — and it gets bigger as the agent gains more tools.</p>

  <h3>1. Attack surface explosion</h3>
  <p>Each integration is a potential prompt injection vector. An agent with access to GitHub + Stripe + email can, if misconfigured, leak data, trigger charges or send unauthorized communications. Access tokens must be scoped to the minimum necessary — read where possible, write only where demonstrably needed.</p>

  <h3>2. Token cost scales with tools</h3>
  <p>Each tool call adds tokens to the context. An agent with 10 active integrations making 5 calls per flow can consume 3–5x more tokens than a simple agent. Monitor cost per session from day 1.</p>

  <h3>3. Persistent memory creates compliance risk</h3>
  <p>GoodMem and Qdrant write context between sessions. In regulated sectors (healthcare, finance, education), this requires retention policy, anonymization and audit. "Memory" without governance is unmanaged personal data.</p>

  <h3>4. Dependency on third-party SLAs</h3>
  <p>If the partner's MCP endpoint goes down, your agent loses that tool. Implement fallback and circuit breaker for critical integrations.</p>

  <hr />

  <h2>Code example: GitHub Agent with ADK</h2>
  <p>Google's official blog provides a direct example. In Python, adding GitHub to your ADK agent looks like this:</p>

  <div class="blog-code-block">

from google.adk.agents import Agent from google.adk.tools.mcp_tool import McpToolset from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPServerParams

GITHUB_TOKEN = “YOUR_GITHUB_TOKEN” # use scoped token (read-only where possible)

root_agent = Agent( model=“gemini-2.0-flash”, name=“github_agent”, instruction=“Help the user query repositories and issues on GitHub”, tools=[ McpToolset( connection_params=StreamableHTTPServerParams( url=“https://api.githubcopilot.com/mcp/”, headers={ “Authorization”: f”Bearer {GITHUB_TOKEN}”, “X-MCP-Toolsets”: “all”, “X-MCP-Read-Only”: “true” # explicit guardrail }, ), ) ], )

The pattern is the same for any integration: swap the endpoint and credentials. The agent doesn’t need to know how GitHub works internally — only what it can do.

  <hr />

  <h2>Connection to A-MAD: where the ADK ecosystem fits</h2>
  <p>In the <strong>A-MAD (AI-Managed Agile Development)</strong> methodology we apply in Autenticare projects, the ADK with integrations specifically solves the <em>autonomous execution</em> layer — the point where the agent stops being a chat assistant and becomes an active participant in the workflow.</p>

  <p>In real projects, we see three adoption patterns that work well with this ecosystem:</p>
  <ul>
    <li><strong>Issue triage agent</strong> — reads GitHub/Linear, classifies by severity, assigns to the right dev, updates Notion. Zero code writing, high operational impact.</li>
    <li><strong>Customer onboarding agent</strong> — queries CRM, generates contract from template, fires email via Mailgun, creates workspace in Notion. A flow that took 2 days takes 20 minutes.</li>
    <li><strong>Financial monitoring agent</strong> — queries Stripe, consolidates metrics, generates report and sends via email. Replaces manual weekly dashboard.</li>
  </ul>

  <p>In all cases, the rule is the same: <strong>observability first, autonomy second</strong>. Install Phoenix or AgentOps before putting the agent in production. Understand the tool-use pattern before removing the human from the loop.</p>

  <hr />

  <h2>Readiness checklist before flipping the switch</h2>
  <ul>
    <li>☐ Access tokens scoped to minimum necessary per integration</li>
    <li>☐ Observability configured (tool-use tracing, session logs)</li>
    <li>☐ Human approval active for irreversible actions (payment, merge, mass email)</li>
    <li>☐ Retention policy defined for persistent memory (Qdrant/GoodMem)</li>
    <li>☐ Fallback implemented for critical integrations</li>
    <li>☐ Prompt injection tests with adversarial inputs before production</li>
    <li>☐ Token cost monitoring per session active</li>
  </ul>

  <blockquote>
    Observability first, autonomy second. Install Phoenix or AgentOps before putting the agent in production — understand the tool-use pattern before removing the human from the loop.
  </blockquote>

Frequently Asked Questions sobre Google ADK: 30+ Integrations for AI Agents

Which platforms does Google ADK now support? Google ADK now connects to over 30 platforms, including GitHub, Stripe, Qdrant, Notion, and Mailgun.

How are ADK integrations configured? Integrations are configured through a McpToolset that points to the partner’s MCP endpoint, with scoped credentials.

What integration categories are available in ADK? ADK offers integrations in categories such as Code & Dev, Project Management, Databases & Vector, Persistent Memory, Observability, Connectors, Payments, Voice & Audio, Email & Messaging, and AI & Datasets.

Which Google Cloud services does ADK offer native integrations with? ADK includes native connectors with Google Cloud services such as BigQuery, Spanner, and Pub/Sub.

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