Connectto Calendly, Google Docs, Firecrawl Deep Research MCP Servers
Create powerful AI workflows by connecting multiple MCP servers including Calendly, Google Docs, Firecrawl Deep Research for enhanced automation capabilities in Klavis AI.
Calendly
Manage scheduling and appointments with your agents.
Google Docs
Google Docs is a word processor included as part of the free, web-based Google Docs Editors suite
Available Tools:
- google_docs_get_document_by_id
- google_docs_get_all_documents
- google_docs_insert_text_at_end
- +2 more tools
Firecrawl Deep Research
A personal research assistant that analyze sources across the web, based on Firecrawl
Available Tools:
- firecrawl_deep_research
Quick Setup Guide
Follow these steps to connect Fireworks AI 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 Fireworks AI and configure authentication settings.
Test & Deploy
Verify your connections work correctly and start using your enhanced AI capabilities.
Fireworks AI + KlavisAI Integration Snippets
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"))
calendly_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.CALENDLY,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
google_docs_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.GOOGLE_DOCS,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
firecrawl_deep_research_mcp_instance = klavis_client.mcp_server.create_server_instance(
server_name=McpServerName.FIRECRAWL_DEEP_RESEARCH,
user_id="1234",
platform_name="Klavis",
connection_type=ConnectionType.STREAMABLE_HTTP,
)
# Get all MCP tools
calendly_tools = klavis_client.mcp_server.list_tools(
server_url=calendly_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
google_docs_tools = klavis_client.mcp_server.list_tools(
server_url=google_docs_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
firecrawl_deep_research_tools = klavis_client.mcp_server.list_tools(
server_url=firecrawl_deep_research_mcp_instance.server_url,
connection_type=ConnectionType.STREAMABLE_HTTP,
format=ToolFormat.OPENAI,
)
# Combine all tools
all_tools = []
all_tools.extend(calendly_tools.tools)
all_tools.extend(google_docs_tools.tools)
all_tools.extend(firecrawl_deep_research_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
)Frequently Asked Questions
Everything you need to know about connecting to these MCP servers
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