Can my agent determine if a sales phone call was successful?

Yes. By providing the specific Call ID and a structured goal query (e.g., 'Did they buy?'), your AI agent triggers the 'analyze_call' tool, running a targeted LLM pass exactly over that transcript to extract the explicit boolean outcome.

What if a voice agent goes off-script on a live call?

You can instruct your agent to forcefully disrupt the conversation. Using the 'end_call' tool, it will immediately pass an interrupt flag and drop the active telecom connection without waiting for the other party.

Can I make AI agent calls directly through the browser instead of standard telephony?

Absolutely. Your agent can execute the 'create_web_call' tool, which bypasses PSTN billing entirely and opens a pure WebRTC signaling socket for direct in-app or browser audio interactions.

Bland AI MCP Server for Google ADK 10 tools — connect in under 2 minutes

Name: Bland AI
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Bland AI as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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="bland_ai_agent",
    instruction=(
        "You help users interact with Bland AI "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Bland AI MCP Server

Connect your Bland AI API key to your AI agent and take full programmatic control over enterprise-grade telephony and conversational voice workflows.

Google ADK natively supports Bland 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

Automated Calling — Dispatch individual conversational voice agents to specific phone numbers, or scale up with bulk telecom batch dispatching.
Call Management & Analysis — Retrieve full historical call logs, pull raw transcripts, end live calls instantly, and forcefully interrogate recordings to extract goal completion statuses.
Inbound & WebRTC — View your purchased PSTN numbers for inbound routing and effortlessly spawn decoupled internet-based WebRTC signaling sockets for browser audio.
Media Extraction — Pull native MP3/WAV recording files directly for quality assurance or CRM logging.

The Bland 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 Bland AI to Google ADK via MCP

Follow these steps to integrate the Bland 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 Bland AI via MCP

Why Use Google ADK with the Bland AI MCP Server

Google ADK provides unique advantages when paired with Bland 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 Bland 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 Bland AI tools with BigQuery, Vertex AI, and Cloud Functions

Bland AI + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Bland AI MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Bland AI and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Bland AI tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Bland 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 Bland AI

Bland AI MCP Tools for Google ADK (10)

These 10 tools become available when you connect Bland AI to Google ADK via MCP:

analyze_call

Interrogate an active recording querying direct goal completion status

create_web_call

Spawn a decoupled internet-based WebRTC signaling socket logic stream

end_call

Force an immediate disconnect disrupting a live AI call

get_batch

Retrieve aggregations profiling the concurrent status of a Bulk Batch

get_call_details

Retrieve explicit variables and exact transcript logic for a completed call

get_recording

Retrieve raw native MP3/WAV links logging exact raw audio

list_calls

Retrieve the full historical log of AI phone calls

list_inbound

Identify available inbound phone numbers currently bridged to an AI agent

send_batch

Dispatch multiple AI agents concurrently scaling bulk telecom arrays

send_call

Dispatch an automated conversational AI agent to a phone number

Example Prompts for Bland AI in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Bland AI immediately.

"Please analyze call ID `c-12345` with the goal query 'Was the customer interested in a demo?'"

"End the currently active phone call ID `c-99999` immediately."

"List all my purchased inbound phone numbers on Bland AI."

Troubleshooting Bland AI MCP Server with Google ADK

Common issues when connecting Bland AI to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Bland AI + Google ADK FAQ

Common questions about integrating Bland AI MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.