Connectto Google Sheets, Jira, Postgres MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Google Sheets, Jira, Postgres for enhanced automation capabilities in Klavis AI.
Google Sheets
Google Sheets is a web-based spreadsheet application that allows users to create, edit, and collaborate on spreadsheets online
Available Tools:
- google_sheets_create_spreadsheet
- google_sheets_get_spreadsheet
- google_sheets_write_to_cell
- +1 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
Postgres
PostgreSQL is a powerful, open source object-relational database system
Available Tools:
- query
Quick Setup Guide
Follow these steps to connect LangChain 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 LangChain and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
LangChain + KlavisAI Integration Snippets
import os
import asyncio
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
llm = ChatOpenAI(model="gpt-4o-mini", api_key=os.getenv("OPENAI_API_KEY"))
google_sheets_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_SHEETS,
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,
)
postgres_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.POSTGRES,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
mcp_client = MultiServerMCPClient({
"google sheets": {
"transport": "streamable_http",
"url": google_sheets_mcp_instance.server_url
},
"jira": {
"transport": "streamable_http",
"url": jira_mcp_instance.server_url
},
"postgres": {
"transport": "streamable_http",
"url": postgres_mcp_instance.server_url
}
})
tools = asyncio.run(mcp_client.get_tools())
agent = create_react_agent(
model=llm,
tools=tools,
)
response = asyncio.run(agent.ainvoke({
"messages": [{"role": "user", "content": "Your query here"}]
}))Frequently Asked Questions
Everything you need to know about connecting to these MCP servers
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