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Documentation Index

Fetch the complete documentation index at: https://www.klavis.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

Prerequisites Before you begin, create an account and get your API Key.

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Getting started

Connect to PostgreSQL databases to execute queries, analyze data, manage tables, and automate database operations through AI agents.
1

Install the SDKs (optional)

pip install klavis
2

Create a Strata MCP Server with PostgreSQL

from klavis import Klavis
from klavis.types import McpServerName

klavis_client = Klavis(api_key="YOUR_API_KEY")

# Create a Strata MCP server with PostgreSQL
response = klavis_client.mcp_server.create_strata_server(
    servers=[McpServerName.POSTGRES],
    user_id="user123"
)
userId specifies whose connected accounts and data you are accessing in Klavis. It should be a unique id for yourself, your team, or your organization.

API Reference

Full Strata API endpoints
3

Authenticate with API Key

klavis_client.mcp_server.set_strata_auth(
    strata_id=response.strata_id,
    server_name=McpServerName.POSTGRES,
    auth_data={
        "api_key": "postgresql://username:password@host:port/database"
    }
)
Use the standard PostgreSQL connection string format: postgresql://username:password@host:port/database
🎉 Your PostgreSQL MCP Server is ready! Once authentication is complete, you can use your MCP server URL with any MCP-compatible client.

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Available Tools

With our progressive discovery approach, Klavis System is capable of enabling all tools for PostgreSQL. Please use the get_tools API for more details. If you find any tool that is missing, please reach out to contact@klavis.ai.

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Next Steps

AI Platform Integrations

Integrate Klavis MCP Servers with leading AI platforms

Integrations

Explore available MCP servers

API Reference

REST endpoints and schemas

White-label Authentication

Customize OAuth flows with your own branding