Connectto Affinity, Plai, OpenRouter MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Affinity, Plai, OpenRouter for enhanced automation capabilities in Klavis AI.
Affinity
Affinity is a relationship intelligence platform that helps teams manage relationships, track deals, and leverage network insights to drive business growth with powerful CRM and relationship mapping capabilities
Available Tools:
- affinity_get_current_user
- affinity_get_all_list_entries_on_a_list
- affinity_get_metadata_on_all_lists
- +20 more tools
Plai
Plai is an AI-powered advertising platform that simplifies creating, managing, and optimizing Facebook, Instagram, and LinkedIn ad campaigns. It provides tools for lead generation, campaign insights, and automated ad management to help businesses scale their digital marketing efforts effectively.
Available Tools:
- plai_create_user_profile
- plai_get_user_profile
- plai_create_link
- +7 more tools
OpenRouter
Access to multiple AI models through a unified API. Generate chat completions, compare model performance, manage usage and costs, get model recommendations, and analyze model capabilities across various providers like OpenAI, Anthropic, Meta, Google, and more
Available Tools:
- openrouter_list_models
- openrouter_search_models
- openrouter_get_model_pricing
- +11 more tools
Quick Setup Guide
Follow these steps to connect Google Gemini to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Connections
Add your desired MCP servers to Gemini and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
Google Gemini + KlavisAI Integration Snippets
import os
from google import genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
client = genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))
user_message = "Your query here"
affinity_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.AFFINITY,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
plai_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.PLAI,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
openrouter_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.OPENROUTER,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get tools from all MCP servers
affinity_tools = klavis_client.mcp_server.list_tools(
server_url=affinity_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
plai_tools = klavis_client.mcp_server.list_tools(
server_url=plai_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
openrouter_tools = klavis_client.mcp_server.list_tools(
server_url=openrouter_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
# Combine all tools
all_tools = []
all_tools.extend(affinity_tools.tools)
all_tools.extend(plai_tools.tools)
all_tools.extend(openrouter_tools.tools)
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=user_message,
config=genai.types.GenerateContentConfig(
tools=all_tools,
),
)Frequently Asked Questions
Everything you need to know about connecting to these MCP servers
Ready to Get Started?
Join developers who are already using KlavisAI to power their Google Gemini applications with these MCP servers.
Start For Free