ConnectTogether AIto Vercel, Motion MCP Servers

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"))

vercel_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.VERCEL,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

motion_mcp_instance = klavis_client.mcp_server.create_server_instance(
    server_name=McpServerName.MOTION,
    user_id="1234",
    connection_type=ConnectionType.STREAMABLE_HTTP,
)

# Get all MCP tools
vercel_tools = klavis_client.mcp_server.list_tools(
    server_url=vercel_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)
motion_tools = klavis_client.mcp_server.list_tools(
    server_url=motion_mcp_instance.server_url,
    connection_type=ConnectionType.STREAMABLE_HTTP,
    format=ToolFormat.OPENAI,
)

# Combine all tools
all_tools = []
all_tools.extend(vercel_tools.tools)
all_tools.extend(motion_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
)