Vectara MCP Server for Google ADK 7 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Vectara 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="vectara_agent",
instruction=(
"You help users interact with Vectara "
"using 7 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 Vectara MCP Server
Connect your Vectara environment to any AI agent to unlock enterprise-grade Retrieval-Augmented Generation (RAG) and semantic search directly inside your conversational IDE or workspace.
Google ADK natively supports Vectara as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 7 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
- Semantic Search — Query your indexed private corpora naturally and return highly relevant, grounded documents without traditional keyword matching limitations.
- Conversational RAG — Execute fully-fledged interactive chats leveraging Vectara's backend to provide detailed, cited answers strictly based on your secure documents.
- Corpus Management — List all available data corpora, retrieve unique keys, and discover the shape of your indexed data environment on the fly.
- Document Auditing — Monitor specific document indexes within a corpus, verify correct ingestions, or permanently delete obsolete files avoiding polluted search results.
The Vectara MCP Server exposes 7 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 Vectara to Google ADK via MCP
Follow these steps to integrate the Vectara 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 7 tools from Vectara via MCP
Why Use Google ADK with the Vectara MCP Server
Google ADK provides unique advantages when paired with Vectara 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 Vectara
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 Vectara tools with BigQuery, Vertex AI, and Cloud Functions
Vectara + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Vectara MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Vectara and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Vectara tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Vectara regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Vectara
Vectara MCP Tools for Google ADK (7)
These 7 tools become available when you connect Vectara to Google ADK via MCP:
delete_corpus_document
This action is irreversible. Permanently removes a document from a corpus
execute_rag_chat
Provide corpus keys and the user query to get a summarized AI response with citations. Executes a RAG-powered chat completion
get_corpus_details
Retrieves metadata and configuration for a specific corpus
list_chat_sessions
Lists previous RAG chat sessions
list_corpora
Lists all corpora (searchable datasets) in the Vectara account
list_corpus_documents
Lists all indexed documents within a specific corpus
perform_semantic_search
Provide one or more comma-separated corpus keys and the query text. Executes a semantic search across one or more corpora
Example Prompts for Vectara in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Vectara immediately.
"List all configured knowledge corpora I have in Vectara."
"Query corpus `cor-81a` for instructions on 'rolling back kubernetes pods' and show only the top 3 best matching results."
"List all active chat context session IDs for the last week."
Troubleshooting Vectara MCP Server with Google ADK
Common issues when connecting Vectara to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkVectara + Google ADK FAQ
Common questions about integrating Vectara 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 Vectara 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 Vectara to Google ADK
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.