Connectto Dropbox, Figma, OpenRouter MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Dropbox, Figma, OpenRouter for enhanced automation capabilities in Klavis AI.
Dropbox
Complete file management solution for Dropbox cloud storage. Upload, download, organize files and folders, manage sharing and collaboration, handle file versions, create file requests, and perform batch operations on your Dropbox files and folders
Available Tools:
- dropbox_list_folder
- dropbox_continue_folder_listing
- dropbox_create_folder
- +40 more tools
Figma
Figma is a collaborative interface design tool for web and mobile applications.
OpenRouter
Access to multiple AI models through a unified API. Generate chat completions, compare model performance, manage usage and costs, get model recommendations, and analyze model capabilities across various providers like OpenAI, Anthropic, Meta, Google, and more
Available Tools:
- openrouter_list_models
- openrouter_search_models
- openrouter_get_model_pricing
- +11 more tools
Quick Setup Guide
Follow these steps to connect LlamaIndex to these MCP servers
Create Your Account
Sign up for KlavisAI to access our MCP server management platform.
Configure Connections
Add your desired MCP servers to LlamaIndex and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
LlamaIndex + KlavisAI Integration Snippets
import os
from klavis import Klavis
from klavis.types import McpServerName, ConnectionType
from llama_index.tools.mcp import (
BasicMCPClient,
get_tools_from_mcp_url,
aget_tools_from_mcp_url,
)
from llama_index.core.agent.workflow import FunctionAgent, AgentWorkflow
# Initialize clients
klavis_client = Klavis(api_key=os.getenv("KLAVIS_API_KEY"))
dropbox_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.DROPBOX,
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,
)
openrouter_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.OPENROUTER,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
dropbox_tools = await aget_tools_from_mcp_url(
dropbox_mcp_instance.server_url,
client=BasicMCPClient(dropbox_mcp_instance.server_url)
)
figma_tools = await aget_tools_from_mcp_url(
figma_mcp_instance.server_url,
client=BasicMCPClient(figma_mcp_instance.server_url)
)
openrouter_tools = await aget_tools_from_mcp_url(
openrouter_mcp_instance.server_url,
client=BasicMCPClient(openrouter_mcp_instance.server_url)
)
dropbox_agent = FunctionAgent(
name="dropbox_agent",
tools=dropbox_tools,
llm=llm,
)
figma_agent = FunctionAgent(
name="figma_agent",
tools=figma_tools,
llm=llm,
)
openrouter_agent = FunctionAgent(
name="openrouter_agent",
tools=openrouter_tools,
llm=llm,
)
workflow = AgentWorkflow(
agents=[dropbox_agent, figma_agent, openrouter_agent],
root_agent="dropbox_agent",
)Frequently Asked Questions
Everything you need to know about connecting to these MCP servers
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