Connectto Salesforce, Jira, Calendly MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Salesforce, Jira, Calendly for enhanced automation capabilities in Klavis AI.
Salesforce
Salesforce is the world's leading customer relationship management (CRM) platform that helps businesses connect with customers, partners, and potential customers
Available Tools:
- salesforce_query
- salesforce_tooling_query
- salesforce_describe_object
- +2 more tools
Jira
Jira is a project management and issue tracking tool developed by Atlassian
Available Tools:
- jira_search
- jira_get_issue
- jira_search_fields
- +11 more tools
Calendly
Manage scheduling and appointments with your agents.
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
import google.generativeai as genai
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
genai.configure(api_key=os.getenv("GOOGLE_AI_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
# Constants
GEMINI_MODEL = "gemini-2.5-flash"
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,
)
jira_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.JIRA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
calendly_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CALENDLY,
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,
)
jira_tools = klavis_client.mcp_server.list_tools(
server_url=jira_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.GEMINI,
)
calendly_tools = klavis_client.mcp_server.list_tools(
server_url=calendly_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(jira_tools.tools)
all_tools.extend(calendly_tools.tools)
model = genai.GenerativeModel(
model_name=GEMINI_MODEL,
tools=all_tools
)
chat = model.start_chat()
response = chat.send_message(user_message)Frequently Asked Questions
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