Connectto Doc2markdown, Figma, Resend MCP Servers

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

Doc2markdown icon

Doc2markdown

featured

Convert any file to markdown using markitdown

Available Tools:

  • convert_document_to_markdown
Figma icon

Figma

featured

Figma is a collaborative interface design tool for web and mobile applications.

Resend icon

Resend

featured

Resend is a modern email API for sending and receiving emails programmatically

Available Tools:

  • resend_send_email
  • resend_create_audience
  • resend_get_audience
  • +12 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

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"))

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,
)

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

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

# Get all MCP tools
doc2markdown_tools = klavis_client.mcp_server.list_tools(
    server_url=doc2markdown_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
figma_tools = klavis_client.mcp_server.list_tools(
    server_url=figma_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
resend_tools = klavis_client.mcp_server.list_tools(
    server_url=resend_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(doc2markdown_tools.tools)
all_tools.extend(figma_tools.tools)
all_tools.extend(resend_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

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