Connectto Postgres, Doc2markdown, Affinity MCP Servers

Create powerful collaborative AI workflows by connecting multiple MCP servers including Postgres, Doc2markdown, Affinity for enhanced multi-agent automation capabilities in Klavis AI.

Postgres icon

Postgres

featured

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

Available Tools:

  • query
Doc2markdown icon

Doc2markdown

featured

Convert any file to markdown using markitdown

Available Tools:

  • convert_document_to_markdown
Affinity icon

Affinity

coming soon

Affinity is a relationship intelligence platform that helps teams manage relationships, track deals, and leverage network insights to drive business growth with powerful CRM and relationship mapping capabilities

Quick Setup Guide

Follow these steps to connect CrewAI to these MCP servers

1

Create Your Account

Sign up for KlavisAI to access our MCP server management platform.

2

Configure Agents & Tools

Set up your CrewAI agents with your desired MCP servers tools and configure authentication settings for collaborative workflows.

3

Deploy Your Crew

Test your multi-agent workflows and start using your enhanced collaborative AI capabilities.

CrewAI + KlavisAI Integration Snippets

import os
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType

# Initialize clients
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,
)

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,
)

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

# Initialize MCP tools for each server
postgres_tools = MCPServerAdapter(postgres_mcp_instance.server_params)
doc2markdown_tools = MCPServerAdapter(doc2markdown_mcp_instance.server_params)
affinity_tools = MCPServerAdapter(affinity_mcp_instance.server_params)

# Create specialized agents for each service
postgres_agent = Agent(
    role="Postgres Specialist",
    goal="Handle all Postgres related tasks and data processing",
    backstory="You are an expert in Postgres operations and data analysis",
    tools=postgres_tools,
    reasoning=True,
    verbose=False
)

doc2markdown_agent = Agent(
    role="Doc2markdown Specialist",
    goal="Handle all Doc2markdown related tasks and data processing",
    backstory="You are an expert in Doc2markdown operations and data analysis",
    tools=doc2markdown_tools,
    reasoning=True,
    verbose=False
)

affinity_agent = Agent(
    role="Affinity Specialist",
    goal="Handle all Affinity related tasks and data processing",
    backstory="You are an expert in Affinity operations and data analysis",
    tools=affinity_tools,
    reasoning=True,
    verbose=False
)

# Define collaborative tasks
research_task = Task(
    description="Gather comprehensive data from all available sources",
    expected_output="Raw data and initial findings from all services",
    agent=postgres_agent,
    markdown=True
)

analysis_task = Task(
    description="Analyze and synthesize the gathered data",
    expected_output="Comprehensive analysis with insights and recommendations",
    agent=doc2markdown_agent,
    markdown=True
)

# Create multi-agent crew
multi_agent_crew = Crew(
    agents=[postgres_agent, doc2markdown_agent, affinity_agent],
    tasks=[research_task, analysis_task],
    verbose=False,
    process=Process.sequential
)

result = multi_agent_crew.kickoff()

Frequently Asked Questions

Everything you need to know about connecting CrewAI to these MCP servers

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