Create powerful AI workflows by connecting multiple MCP servers including Unified MCP, Exa, Mem0 for enhanced automation capabilities in Klavis AI.
Klavis AI unified MCP server that provides access to multiple tools and capabilities through a single endpoint
Exa is an AI-powered search engine designed for AI applications. Use neural search to understand meaning and context, find similar content, get direct answers with citations, and conduct comprehensive research with structured analysis
Mem0 is an intelligent memory layer for AI applications that provides long-term memory storage and retrieval. Store code snippets, implementation details, and programming knowledge for seamless context retention across conversations
Follow these steps to connect Fireworks AI to these MCP servers
Sign up for KlavisAI to access our MCP server management platform.
Add your desired MCP servers to Fireworks AI and configure authentication settings.
Verify your connections work correctly and start using your enhanced AI capabilities.
import os
import json
from fireworks.client import Fireworks
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType, ToolFormat
# Initialize clients
fireworks_client = Fireworks(api_key=os.getenv("FIREWORKS_API_KEY"))
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
unified_mcp_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.UNIFIED_MCP,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
exa_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.EXA,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
mem0_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.MEM0,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get all MCP tools
unified_mcp_tools = klavis_client.mcp_server.list_tools(
server_url=unified_mcp_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
exa_tools = klavis_client.mcp_server.list_tools(
server_url=exa_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
mem0_tools = klavis_client.mcp_server.list_tools(
server_url=mem0_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(unified_mcp_tools.tools)
all_tools.extend(exa_tools.tools)
all_tools.extend(mem0_tools.tools)
messages = [
{"role": "system", "content": "You are a helpful assistant with access to multiple data sources."},
{"role": "user", "content": user_message}
]
response = fireworks_client.chat.completions.create(
model="accounts/fireworks/models/llama-v3p1-70b-instruct",
messages=messages,
tools=all_tools
)
Everything you need to know about connecting to these MCP servers
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