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Connectto Postgres, Doc2markdown, GitHub MCP Servers

Create powerful AI workflows by connecting multiple MCP servers including Postgres, Doc2markdown, GitHub for enhanced automation capabilities in Klavis AI.

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Postgres icon

Postgres

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

Available Tools:

  • query
Doc2markdown icon

Doc2markdown

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Convert any file to markdown using markitdown

Available Tools:

  • convert_document_to_markdown
GitHub icon

GitHub

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Enhanced GitHub MCP Server

Available Tools:

  • github_get_me
  • github_get_issue
  • github_search_issues
  • +31 more tools

Quick Setup Guide

Follow these steps to connect Google Gemini 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 Gemini and configure authentication settings.

3

Test & Deploy

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

Google Gemini + KlavisAI Integration Snippets

View Documentation
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"

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,
)

doc2markdown_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.DOC2MARKDOWN,
    user_id="1234",
    platform_name="Klavis",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

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

# Get tools from all MCP servers
postgres_tools = klavis_client.mcp_server.list_tools(
    server_url=postgres_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
doc2markdown_tools = klavis_client.mcp_server.list_tools(
    server_url=doc2markdown_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)
github_tools = klavis_client.mcp_server.list_tools(
    server_url=github_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.GEMINI,
)

# Combine all tools
all_tools = []
all_tools.extend(postgres_tools.tools)
all_tools.extend(doc2markdown_tools.tools)
all_tools.extend(github_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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