KlavisAIKlavisAI
Sign Up

Connectto Postgres, Gmail, Google Docs MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Postgres, Gmail, Google Docs for enhanced automation capabilities in Klavis AI.

Get Started FreeView All MCP Servers
Postgres icon

Postgres

featured

PostgreSQL is a powerful, open source object-relational database system

Available Tools:

  • query
Gmail icon

Gmail

featured

Gmail is a free email service provided by Google

Available Tools:

  • send_email
  • draft_email
  • read_email
  • +5 more tools
Google Docs icon

Google Docs

featured

Google Docs is a word processor included as part of the free, web-based Google Docs Editors suite

Available Tools:

  • google_docs_get_document_by_id
  • google_docs_get_all_documents
  • google_docs_insert_text_at_end
  • +2 more tools

Quick Setup Guide

Follow these steps to connect Together AI 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 Together AI and configure authentication settings.

3

Test & Deploy

Verify your connections work correctly and start using your enhanced AI capabilities.

Together AI + KlavisAI Integration Snippets

View Documentation
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"))

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,
)

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

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

# Get all MCP tools
postgres_tools = klavis_client.mcp_server.list_tools(
    server_url=postgres_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
gmail_tools = klavis_client.mcp_server.list_tools(
    server_url=gmail_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
google_docs_tools = klavis_client.mcp_server.list_tools(
    server_url=google_docs_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(postgres_tools.tools)
all_tools.extend(gmail_tools.tools)
all_tools.extend(google_docs_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

Ready to Get Started?

Join developers who are already using KlavisAI to power their Together AI applications with these MCP servers.

Start For Free