Connectto Google Sheets, Postgres, Gong MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Google Sheets, Postgres, Gong 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
Postgres
PostgreSQL is a powerful, open source object-relational database system
Available Tools:
- query
Gong
Gong is a revenue intelligence platform that captures and analyzes all revenue-related interactions to help sales teams close more deals. It provides conversation analytics, deal insights, and sales performance tracking through call recordings and transcripts
Available Tools:
- gong_get_transcripts_by_user
- gong_get_extensive_data
- gong_get_call_transcripts
- +2 more tools
Quick Setup Guide
Follow these steps to connect Together AI 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 Together AI and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
Together AI + KlavisAI Integration Snippets
import os
import json
from together import Together
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
together_client = Together(api_key=os.getenv("TOGETHER_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_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,
)
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,
)
gong_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GONG,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get all MCP tools
google_sheets_tools = klavis_client.mcp_server.list_tools(
server_url=google_sheets_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
postgres_tools = klavis_client.mcp_server.list_tools(
server_url=postgres_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
gong_tools = klavis_client.mcp_server.list_tools(
server_url=gong_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(google_sheets_tools.tools)
all_tools.extend(postgres_tools.tools)
all_tools.extend(gong_tools.tools)
messages = [
{"role": "system", "content": "You are a helpful AI assistant with access to multiple data sources."},
{"role": "user", "content": user_message}
]
response = together_client.chat.completions.create(
model="meta-llama/Llama-2-70b-chat-hf",
messages=messages,
tools=all_tools
)Frequently Asked Questions
Everything you need to know about connecting to these MCP servers
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