Cohere (Embed & Rerank) MCP Server for Google ADK 6 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Cohere (Embed & Rerank) as an MCP tool provider through the 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="cohere_embed_rerank_agent",
instruction=(
"You help users interact with Cohere (Embed & Rerank) "
"using 6 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 Cohere (Embed & Rerank) MCP Server
Connect your Cohere account to any AI agent and take full control of your enterprise AI and RAG workflows through natural conversation.
Google ADK natively supports Cohere (Embed & Rerank) as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 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
- Text Embeddings — Generate precise dense vector shapes for plain strings to power semantic search and knowledge retrieval
- Semantic Reranking — Structure contextual chunks by priority ordering documents against specific queries for improved RAG accuracy
- Conversational AI — Execute formatted conversational transformations using Cohere's generation limits and state-of-the-art LLMs
- Text Classification — Categorize inputs into predefined labels using few-shot training blocks and extract confidence scores
- Tokenization — Retrieve exact structural segmentation of NLP contexts to audit token counts and model dictionaries
- Model Registry — Enumerate available Cohere models and hashes to verify API availability based on your plan
The Cohere (Embed & Rerank) MCP Server exposes 6 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 Cohere (Embed & Rerank) to Google ADK via MCP
Follow these steps to integrate the Cohere (Embed & Rerank) 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 6 tools from Cohere (Embed & Rerank) via MCP
Why Use Google ADK with the Cohere (Embed & Rerank) MCP Server
Google ADK provides unique advantages when paired with Cohere (Embed & Rerank) 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 Cohere (Embed & Rerank)
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 Cohere (Embed & Rerank) tools with BigQuery, Vertex AI, and Cloud Functions
Cohere (Embed & Rerank) + Google ADK Use Cases
Practical scenarios where Google ADK combined with the Cohere (Embed & Rerank) MCP Server delivers measurable value.
Enterprise data agents: ADK agents query Cohere (Embed & Rerank) and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine Cohere (Embed & Rerank) tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query Cohere (Embed & Rerank) regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Cohere (Embed & Rerank)
Cohere (Embed & Rerank) MCP Tools for Google ADK (6)
These 6 tools become available when you connect Cohere (Embed & Rerank) to Google ADK via MCP:
chat_completion
Execute explicitly formatted conversational transformations
classify_texts
Enumerate explicitly mapped string classes evaluating static limits
embed_texts
Identify precise dense vector shapes mapping semantic limits
list_models
Inspect internal properties detailing API availability
rerank_documents
Discover explicit routing arrays structuring specific contextual chunks
tokenize_text
Retrieve the exact structural segmentation limiting NLP contexts
Example Prompts for Cohere (Embed & Rerank) in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with Cohere (Embed & Rerank) immediately.
"Generate embeddings for these texts: ['Hello world', 'Artificial Intelligence']"
"Rerank these documents for query 'Best pizza in NY': ['Pizza hut review', 'Joe's Pizza is the local favorite']"
"How many tokens are in the text: 'The quick brown fox jumps over the lazy dog'?"
Troubleshooting Cohere (Embed & Rerank) MCP Server with Google ADK
Common issues when connecting Cohere (Embed & Rerank) to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkCohere (Embed & Rerank) + Google ADK FAQ
Common questions about integrating Cohere (Embed & Rerank) 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 Cohere (Embed & Rerank) 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 Cohere (Embed & Rerank) to Google ADK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.