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Connectto Gong, Airtable, Mem0 MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Gong, Airtable, Mem0 for enhanced automation capabilities in Klavis AI.

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Gong icon

Gong

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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
Airtable icon

Airtable

featured

Airtable is a cloud-based database and spreadsheet platform that combines the flexibility of a spreadsheet with the power of a database, enabling teams to organize, track, and collaborate on projects with customizable views and powerful automation features

Available Tools:

  • airtable_list_bases_info
  • airtable_list_tables_info
  • airtable_create_table
  • +8 more tools
Mem0 icon

Mem0

featured

Mem0 is an intelligent memory layer for AI applications that provides long-term memory storage and retrieval. Store code snippets, implementation details, and programming knowledge for seamless context retention across conversations

Available Tools:

  • mem0_add_memory
  • mem0_get_all_memories
  • mem0_search_memories
  • +2 more tools

Quick Setup Guide

Follow these steps to connect your AI agents 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 your AI client and configure authentication settings.

3

Test & Deploy

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

Integrate in minutes, Scale to millions

View Documentation
from klavis import Klavis

klavis_client = Klavis(api_key="KLAVIS_API_KEY")

servers = ["Gong", "Airtable", "Mem0"]
responses = []

for server in servers:
    mcp_server = klavis_client.mcp_server.create_server_instance(
        server_name=server,
        user_id="<USER_ID>",
        platform_name="<PLATFORM_NAME>"
    )
    responses.append(mcp_server)

Frequently Asked Questions

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