How to Use the Bible API MCP in Google ADK

Connect Gemini's 1M token window to the Bible API with Google ADK for deep text analysis.

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Connect Bible API MCP to Google ADK

Create your Vinkius account to connect Bible API to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Bible API with Google ADK

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Query translations using Google ADK and this MCP Server

The `list_bibles` tool lists all available translations and languages, while `list_bible_books` lists the books within a chosen version. This lets Gemini analyze how language evolved across centuries by comparing translations side-by-side. Because Gemini handles massive context windows, you can load multiple versions simultaneously. The tools return structured data that feeds directly into your Google Cloud data pipelines.

Extract precise verses for enterprise pipelines

The `get_bible_verse` tool extracts individual verses, and `get_bible_details` provides the publisher and language metadata. This allows your enterprise agent to cite its sources with perfect accuracy when generating reports. You avoid hallucinated quotes by forcing the model to fetch the exact text from the API. The toolset integrates with your existing Vertex AI setups without extra configuration.

Search historical documents at scale

The `search_bible_text` tool scans entire translations for specific keywords, and `get_bible_chapter` pulls the surrounding context. Your agent can perform complex thematic analysis across thousands of pages in seconds. This MCP Server bypasses the need to store massive text files in your own database. Your agent queries the live API as needed, keeping your storage costs low.

Setup guide

Set up Bible API MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Bible API tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Bible API_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Bible API tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bible API. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Bible API MCP in Google ADK

Use the McpToolset class with the server HTTP URL and pass it to your LlmAgent. The ADK maps the scripture tools from this MCP Server directly to Gemini's function calling interface.

Yes, you can use the optional tool name filter in the ADK setup. This restricts the agent to search_bible_text and blocks other actions.

Yes. Your agent can fetch verses using the tools and then write those records directly into a BigQuery table for downstream analytics.

This server works over both Stdio and HTTP transports. For cloud deployments, the HTTP transport is the standard choice.

Your search terms and version selections pass through a zero-trust gateway. No query history is kept, and the transport layer uses TLS encryption to protect your data.

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