Connectto Salesforce, Exa, Google Jobs MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Salesforce, Exa, Google Jobs for enhanced automation capabilities in Klavis AI.

Salesforce icon

Salesforce

featured

Salesforce is the world's leading customer relationship management (CRM) platform that helps businesses connect with customers, partners, and potential customers

Available Tools:

  • salesforce_get_accounts
  • salesforce_create_account
  • salesforce_update_account
  • +24 more tools
Exa icon

Exa

featured

Exa is an AI-powered search engine designed for AI applications. Use neural search to understand meaning and context, find similar content, get direct answers with citations, and conduct comprehensive research with structured analysis

Available Tools:

  • exa_search
  • exa_get_contents
  • exa_find_similar
  • +2 more tools
Google Jobs icon

Google Jobs

featured

Google Jobs is a comprehensive job search platform that aggregates listings from across the web. Search for jobs by location, company, employment type, and more, with detailed information about requirements, benefits, and application processes

Available Tools:

  • google_jobs_search
  • google_jobs_get_details
  • google_jobs_search_by_company
  • +2 more tools

Quick Setup Guide

Follow these steps to connect Google Gemini to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Connections

Add your desired MCP servers to Gemini and configure authentication settings.

3

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"

salesforce_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.SALESFORCE,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

exa_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.EXA,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

google_jobs_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.GOOGLE_JOBS,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Get tools from all MCP servers
salesforce_tools = klavis_client.mcp_server.list_tools(
    server_url=salesforce_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
exa_tools = klavis_client.mcp_server.list_tools(
    server_url=exa_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
google_jobs_tools = klavis_client.mcp_server.list_tools(
    server_url=google_jobs_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(salesforce_tools.tools)
all_tools.extend(exa_tools.tools)
all_tools.extend(google_jobs_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