# How to integrate Scheduleonce MCP with LlamaIndex ```json { "title": "How to integrate Scheduleonce MCP with LlamaIndex", "toolkit": "Scheduleonce", "toolkit_slug": "scheduleonce", "framework": "LlamaIndex", "framework_slug": "llama-index", "url": "https://composio.dev/toolkits/scheduleonce/framework/llama-index", "markdown_url": "https://composio.dev/toolkits/scheduleonce/framework/llama-index.md", "updated_at": "2026-03-29T06:48:52.795Z" } ``` ## Introduction This guide walks you through connecting Scheduleonce to LlamaIndex using the Composio tool router. By the end, you'll have a working Scheduleonce agent that can book a meeting with john doe, list all upcoming bookings this week, cancel tomorrow's meeting with client through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Scheduleonce account through Composio's Scheduleonce MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Scheduleonce with - [OpenAI Agents SDK](https://composio.dev/toolkits/scheduleonce/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/scheduleonce/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/scheduleonce/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/scheduleonce/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/scheduleonce/framework/codex) - [OpenClaw](https://composio.dev/toolkits/scheduleonce/framework/openclaw) - [Hermes](https://composio.dev/toolkits/scheduleonce/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/scheduleonce/framework/cli) - [Google ADK](https://composio.dev/toolkits/scheduleonce/framework/google-adk) - [LangChain](https://composio.dev/toolkits/scheduleonce/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/scheduleonce/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/scheduleonce/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/scheduleonce/framework/crew-ai) ## TL;DR Here's what you'll learn: - Set your OpenAI and Composio API keys - Install LlamaIndex and Composio packages - Create a Composio Tool Router session for Scheduleonce - Connect LlamaIndex to the Scheduleonce MCP server - Build a Scheduleonce-powered agent using LlamaIndex - Interact with Scheduleonce through natural language ## What is LlamaIndex? LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools. Key features include: - ReAct Agent: Reasoning and acting pattern for tool-using agents - MCP Tools: Native support for Model Context Protocol - Context Management: Maintain conversation context across interactions - Async Support: Built for async/await patterns ## What is the Scheduleonce MCP server, and what's possible with it? The Scheduleonce MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Scheduleonce account. It provides structured and secure access so your agent can perform Scheduleonce operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SCHEDULEONCE_BOOK_TIME_SLOT` | Book Time Slot | Tool to book a time slot on a booking calendar in OnceHub. Use when you need to schedule a meeting by booking one of the available time slots. First retrieve available time slots using 'Get available time slots', then use this tool to book one of those slots with guest information. | | `SCHEDULEONCE_CANCEL_BOOKING` | Cancel Booking | Tool to cancel a booking by ID in OnceHub. Use when you need to cancel an existing booking, optionally providing a cancellation reason and controlling whether to send cancellation email notifications. | | `SCHEDULEONCE_CREATE_CONTACT` | Create Contact | Tool to create a new contact in ScheduleOnce. Use when you need to add a contact with email, first name, and last name. Additional fields like company, phone, and address details can be optionally provided. | | `SCHEDULEONCE_CREATE_ONE_TIME_LINK_FOR_BOOKING_CALENDAR` | Create One-Time Link for Booking Calendar | Tool to create a one-time booking link for a booking calendar in OnceHub. Use when you need to generate a unique, single-use booking link for a customer. One-time links are good for one booking only and automatically expire after one year if not used. The booking calendar must be published to create one-time links. | | `SCHEDULEONCE_CREATE_USER` | Create User | Tool to create a new user account in OnceHub. Use when you need to add a new user with first name, last name, and email. Optional role can be specified. | | `SCHEDULEONCE_DELETE_CONTACT` | Delete Contact | Tool to delete a contact by ID from OnceHub. Use when you need to permanently remove a contact from the system. | | `SCHEDULEONCE_DELETE_USER` | Delete User | Tool to delete a user account from OnceHub. Use when you need to permanently remove a user from the system. | | `SCHEDULEONCE_GET_AVAILABLE_TIME_SLOTS` | Get Available Time Slots | Tool to retrieve available time slots for a booking calendar from OnceHub. Use when you need to check availability for scheduling appointments within a specific date range (maximum 30 days). Returns real-time availability based on booking rules and participant calendars. | | `SCHEDULEONCE_GET_SINGLE_BOOKING` | Get Single Booking | Tool to retrieve a single booking by ID from OnceHub. Use when you need to fetch complete booking details including timing, customer information, location, status, and form submission data. | | `SCHEDULEONCE_GET_SINGLE_BOOKING_CALENDAR` | Get Single Booking Calendar | Tool to retrieve a single booking calendar by ID from OnceHub. Use when you need to fetch detailed information about a specific booking calendar including its subject, name, URL, host, published status, and duration. | | `SCHEDULEONCE_GET_SINGLE_CONTACT` | Get Single Contact | Tool to retrieve a single contact by ID from OnceHub. Use when you need to fetch complete contact details including personal information, location data, and custom fields. | | `SCHEDULEONCE_GET_SINGLE_MASTER_PAGE` | Get Single Master Page | Tool to retrieve a single master page by ID from OnceHub. Use when you need to fetch complete master page details including name, label, URL, and active status. | | `SCHEDULEONCE_GET_SINGLE_USER` | Get Single User | Tool to retrieve a single user by ID from OnceHub. Use when you need to fetch detailed information about a specific user including their name, email, status, role, timezone, and team associations. | | `SCHEDULEONCE_GET_USER_SCHEDULING_AVAILABILITY` | Get User Scheduling Availability | Tool to get user scheduling availability from OnceHub. Use when you need to retrieve a user's weekly schedule, working hours, and any date-specific overrides. | | `SCHEDULEONCE_LIST_ALL_BOOKING_CALENDARS` | List All Booking Calendars | Tool to list all booking calendars in the account. Use when you need to retrieve all booking calendars with optional cursor-based pagination. | | `SCHEDULEONCE_LIST_ALL_BOOKING_PAGES` | List All Booking Pages | Tool to list all booking pages in the account. Use when you need to retrieve all booking pages with optional cursor-based pagination. | | `SCHEDULEONCE_LIST_ALL_BOOKINGS` | List All Bookings | Tool to list all bookings in the account. Use when you need to retrieve bookings with optional filtering by time ranges, pagination, or expansion of related objects. | | `SCHEDULEONCE_LIST_ALL_CONTACTS` | List All Contacts | Tool to list all contacts in the OnceHub account. Use when you need to retrieve contact information with optional filtering by creation time, update time, owner, or cursor-based pagination. | | `SCHEDULEONCE_LIST_ALL_EVENT_TYPES` | List All Event Types | Tool to list all event types in the account. Use when you need to retrieve all event types with optional cursor-based pagination to understand available event type options. | | `SCHEDULEONCE_LIST_ALL_MASTER_PAGES` | List All Master Pages | Tool to list all master pages in the account. Use when you need to retrieve all master pages with optional cursor-based pagination. | | `SCHEDULEONCE_LIST_ALL_TEAMS` | List All Teams | Tool to list all teams in the OnceHub account. Use when you need to retrieve team information with optional cursor-based pagination. | | `SCHEDULEONCE_LIST_ALL_USERS` | List All Users | Tool to list all users in the OnceHub account. Use when you need to retrieve user information with optional cursor-based pagination. | | `SCHEDULEONCE_MARK_BOOKING_AS_NO_SHOW` | Mark Booking as No-Show | Tool to mark a completed booking as no-show in OnceHub. Use when the customer did not attend the scheduled meeting and you need to update the booking status to reflect the no-show. | | `SCHEDULEONCE_TEST_API_KEY` | Test API Key | Tool to validate API key authentication for OnceHub. Use when you need to verify that your API key is valid and active before making other API calls to the platform. | | `SCHEDULEONCE_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact in ScheduleOnce. Use when you need to modify contact information such as name, email, company, or phone number. | | `SCHEDULEONCE_UPDATE_USER` | Update User | Tool to update an existing user in OnceHub. Use when you need to modify user information such as name, email, role, or timezone. | | `SCHEDULEONCE_UPDATE_USER_SCHEDULING_AVAILABILITY` | Update User Scheduling Availability | Tool to update user scheduling availability in OnceHub. Use when you need to modify a user's weekly schedule, set working hours for specific days, or add date-specific overrides for holidays or special events. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Scheduleonce MCP server is an implementation of the Model Context Protocol that connects your AI agent to Scheduleonce. It provides structured and secure access so your agent can perform Scheduleonce operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Python 3.8/Node 16 or higher installed - A Composio account with the API key - An OpenAI API key - A Scheduleonce account and project - Basic familiarity with async Python/Typescript ### 1. Getting API Keys for OpenAI, Composio, and Scheduleonce No description provided. ### 2. Installing dependencies No description provided. ```python pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv ``` ```typescript npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv ``` ### 3. Set environment variables Create a .env file in your project root: These credentials will be used to: - Authenticate with OpenAI's GPT-5 model - Connect to Composio's Tool Router - Identify your Composio user session for Scheduleonce access ```bash OPENAI_API_KEY=your-openai-api-key COMPOSIO_API_KEY=your-composio-api-key COMPOSIO_USER_ID=your-user-id ``` ### 4. Import modules No description provided. ```python import asyncio import os import dotenv from composio import Composio from composio_llamaindex import LlamaIndexProvider from llama_index.core.agent.workflow import ReActAgent from llama_index.core.workflow import Context from llama_index.llms.openai import OpenAI from llama_index.tools.mcp import BasicMCPClient, McpToolSpec dotenv.load_dotenv() ``` ```typescript import "dotenv/config"; import readline from "node:readline/promises"; import { stdin as input, stdout as output } from "node:process"; import { Composio } from "@composio/core"; import { mcp } from "@llamaindex/tools"; import { agent as createAgent } from "@llamaindex/workflow"; import { openai } from "@llamaindex/openai"; dotenv.config(); ``` ### 5. Load environment variables and initialize Composio No description provided. ```python OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not OPENAI_API_KEY: raise ValueError("OPENAI_API_KEY is not set in the environment") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set in the environment") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set in the environment") ``` ```typescript const OPENAI_API_KEY = process.env.OPENAI_API_KEY; const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY; const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID; if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set"); if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set"); ``` ### 6. Create a Tool Router session and build the agent function What's happening here: - We create a Composio client using your API key and configure it with the LlamaIndex provider - We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, scheduleonce) - The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools - LlamaIndex will connect to this endpoint to dynamically discover and use the available Scheduleonce tools. - The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent. ```python async def build_agent() -> ReActAgent: composio_client = Composio( api_key=COMPOSIO_API_KEY, provider=LlamaIndexProvider(), ) session = composio_client.create( user_id=COMPOSIO_USER_ID, toolkits=["scheduleonce"], ) mcp_url = session.mcp.url print(f"Composio MCP URL: {mcp_url}") mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY}) mcp_tool_spec = McpToolSpec(client=mcp_client) tools = await mcp_tool_spec.to_tool_list_async() llm = OpenAI(model="gpt-5") description = "An agent that uses Composio Tool Router MCP tools to perform Scheduleonce actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Scheduleonce actions. """ return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True) ``` ```typescript async function buildAgent() { console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`); console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`); const composio = new Composio({ apiKey: COMPOSIO_API_KEY, provider: new LlamaindexProvider(), }); const session = await composio.create( COMPOSIO_USER_ID!, { toolkits: ["scheduleonce"], }, ); const mcpUrl = session.mcp.url; console.log(`Composio Tool Router MCP URL: ${mcpUrl}`); const server = mcp({ url: mcpUrl, clientName: "composio_tool_router_with_llamaindex", requestInit: { headers: { "x-api-key": COMPOSIO_API_KEY!, }, }, // verbose: true, }); const tools = await server.tools(); const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" }); const agent = createAgent({ name: "composio_tool_router_with_llamaindex", description : "An agent that uses Composio Tool Router MCP tools to perform actions.", systemPrompt: "You are a helpful assistant connected to Composio Tool Router."+ "Use the available tools to answer user queries and perform Scheduleonce actions." , llm, tools, }); return agent; } ``` ### 7. Create an interactive chat loop No description provided. ```python async def chat_loop(agent: ReActAgent) -> None: ctx = Context(agent) print("Type 'quit', 'exit', or Ctrl+C to stop.") while True: try: user_input = input("\nYou: ").strip() except (KeyboardInterrupt, EOFError): print("\nBye!") break if not user_input or user_input.lower() in {"quit", "exit"}: print("Bye!") break try: print("Agent: ", end="", flush=True) handler = agent.run(user_input, ctx=ctx) async for event in handler.stream_events(): # Stream token-by-token from LLM responses if hasattr(event, "delta") and event.delta: print(event.delta, end="", flush=True) # Show tool calls as they happen elif hasattr(event, "tool_name"): print(f"\n[Using tool: {event.tool_name}]", flush=True) # Get final response response = await handler print() # Newline after streaming except KeyboardInterrupt: print("\n[Interrupted]") continue except Exception as e: print(f"\nError: {e}") ``` ```typescript async function chatLoop(agent: ReturnType) { const rl = readline.createInterface({ input, output }); console.log("Type 'quit' or 'exit' to stop."); while (true) { let userInput: string; try { userInput = (await rl.question("\nYou: ")).trim(); } catch { console.log("\nAgent: Bye!"); break; } if (!userInput) { continue; } const lower = userInput.toLowerCase(); if (lower === "quit" || lower === "exit") { console.log("Agent: Bye!"); break; } try { process.stdout.write("Agent: "); const stream = agent.runStream(userInput); let finalResult: any = null; for await (const event of stream) { // The event.data contains the streamed content const data: any = event.data; // Check for streaming delta content if (data?.delta) { process.stdout.write(data.delta); } // Store final result for fallback if (data?.result || data?.message) { finalResult = data; } } // If no streaming happened, show the final result if (finalResult) { const answer = finalResult.result ?? finalResult.message?.content ?? finalResult.message ?? ""; if (answer && typeof answer === "string" && !answer.includes("[object")) { process.stdout.write(answer); } } console.log(); // New line after streaming completes } catch (err: any) { console.error("\nAgent error:", err?.message ?? err); } } rl.close(); } ``` ### 8. Define the main entry point What's happening here: - We're orchestrating the entire application flow - The agent gets built with proper error handling - Then we kick off the interactive chat loop so you can start talking to Scheduleonce ```python async def main() -> None: agent = await build_agent() await chat_loop(agent) if __name__ == "__main__": # Handle Ctrl+C gracefully signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0))) try: asyncio.run(main()) except KeyboardInterrupt: print("\nBye!") ``` ```typescript async function main() { try { const agent = await buildAgent(); await chatLoop(agent); } catch (err) { console.error("Failed to start agent:", err); process.exit(1); } } main(); ``` ### 9. Run the agent When prompted, authenticate and authorise your agent with Scheduleonce, then start asking questions. ```bash python llamaindex_agent.py ``` ```typescript npx ts-node llamaindex-agent.ts ``` ## Complete Code ```python import asyncio import os import signal import dotenv from composio import Composio from composio_llamaindex import LlamaIndexProvider from llama_index.core.agent.workflow import ReActAgent from llama_index.core.workflow import Context from llama_index.llms.openai import OpenAI from llama_index.tools.mcp import BasicMCPClient, McpToolSpec dotenv.load_dotenv() OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not OPENAI_API_KEY: raise ValueError("OPENAI_API_KEY is not set") if not COMPOSIO_API_KEY: raise ValueError("COMPOSIO_API_KEY is not set") if not COMPOSIO_USER_ID: raise ValueError("COMPOSIO_USER_ID is not set") async def build_agent() -> ReActAgent: composio_client = Composio( api_key=COMPOSIO_API_KEY, provider=LlamaIndexProvider(), ) session = composio_client.create( user_id=COMPOSIO_USER_ID, toolkits=["scheduleonce"], ) mcp_url = session.mcp.url print(f"Composio MCP URL: {mcp_url}") mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY}) mcp_tool_spec = McpToolSpec(client=mcp_client) tools = await mcp_tool_spec.to_tool_list_async() llm = OpenAI(model="gpt-5") description = "An agent that uses Composio Tool Router MCP tools to perform Scheduleonce actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Scheduleonce actions. """ return ReActAgent( tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True, ); async def chat_loop(agent: ReActAgent) -> None: ctx = Context(agent) print("Type 'quit', 'exit', or Ctrl+C to stop.") while True: try: user_input = input("\nYou: ").strip() except (KeyboardInterrupt, EOFError): print("\nBye!") break if not user_input or user_input.lower() in {"quit", "exit"}: print("Bye!") break try: print("Agent: ", end="", flush=True) handler = agent.run(user_input, ctx=ctx) async for event in handler.stream_events(): # Stream token-by-token from LLM responses if hasattr(event, "delta") and event.delta: print(event.delta, end="", flush=True) # Show tool calls as they happen elif hasattr(event, "tool_name"): print(f"\n[Using tool: {event.tool_name}]", flush=True) # Get final response response = await handler print() # Newline after streaming except KeyboardInterrupt: print("\n[Interrupted]") continue except Exception as e: print(f"\nError: {e}") async def main() -> None: agent = await build_agent() await chat_loop(agent) if __name__ == "__main__": # Handle Ctrl+C gracefully signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0))) try: asyncio.run(main()) except KeyboardInterrupt: print("\nBye!") ``` ```typescript import "dotenv/config"; import readline from "node:readline/promises"; import { stdin as input, stdout as output } from "node:process"; import { Composio } from "@composio/core"; import { LlamaindexProvider } from "@composio/llamaindex"; import { mcp } from "@llamaindex/tools"; import { agent as createAgent } from "@llamaindex/workflow"; import { openai } from "@llamaindex/openai"; dotenv.config(); const OPENAI_API_KEY = process.env.OPENAI_API_KEY; const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY; const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID; if (!OPENAI_API_KEY) { throw new Error("OPENAI_API_KEY is not set in the environment"); } if (!COMPOSIO_API_KEY) { throw new Error("COMPOSIO_API_KEY is not set in the environment"); } if (!COMPOSIO_USER_ID) { throw new Error("COMPOSIO_USER_ID is not set in the environment"); } async function buildAgent() { console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`); console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`); const composio = new Composio({ apiKey: COMPOSIO_API_KEY, provider: new LlamaindexProvider(), }); const session = await composio.create( COMPOSIO_USER_ID!, { toolkits: ["scheduleonce"], }, ); const mcpUrl = session.mcp.url; console.log(`Composio Tool Router MCP URL: ${mcpUrl}`); const server = mcp({ url: mcpUrl, clientName: "composio_tool_router_with_llamaindex", requestInit: { headers: { "x-api-key": COMPOSIO_API_KEY!, }, }, // verbose: true, }); const tools = await server.tools(); const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" }); const agent = createAgent({ name: "composio_tool_router_with_llamaindex", description: "An agent that uses Composio Tool Router MCP tools to perform actions.", systemPrompt: "You are a helpful assistant connected to Composio Tool Router."+ "Use the available tools to answer user queries and perform Scheduleonce actions." , llm, tools, }); return agent; } async function chatLoop(agent: ReturnType) { const rl = readline.createInterface({ input, output }); console.log("Type 'quit' or 'exit' to stop."); while (true) { let userInput: string; try { userInput = (await rl.question("\nYou: ")).trim(); } catch { console.log("\nAgent: Bye!"); break; } if (!userInput) { continue; } const lower = userInput.toLowerCase(); if (lower === "quit" || lower === "exit") { console.log("Agent: Bye!"); break; } try { process.stdout.write("Agent: "); const stream = agent.runStream(userInput); let finalResult: any = null; for await (const event of stream) { // The event.data contains the streamed content const data: any = event.data; // Check for streaming delta content if (data?.delta) { process.stdout.write(data.delta); } // Store final result for fallback if (data?.result || data?.message) { finalResult = data; } } // If no streaming happened, show the final result if (finalResult) { const answer = finalResult.result ?? finalResult.message?.content ?? finalResult.message ?? ""; if (answer && typeof answer === "string" && !answer.includes("[object")) { process.stdout.write(answer); } } console.log(); // New line after streaming completes } catch (err: any) { console.error("\nAgent error:", err?.message ?? err); } } rl.close(); } async function main() { try { const agent = await buildAgent(); await chatLoop(agent); } catch (err: any) { console.error("Failed to start agent:", err?.message ?? err); process.exit(1); } } main(); ``` ## Conclusion You've successfully connected Scheduleonce to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways: - Tool Router dynamically exposes Scheduleonce tools through an MCP endpoint - LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations - The agent becomes more capable without increasing prompt size - Async Python provides clean, efficient execution of agent workflows You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter. ## How to build Scheduleonce MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/scheduleonce/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/scheduleonce/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/scheduleonce/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/scheduleonce/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/scheduleonce/framework/codex) - [OpenClaw](https://composio.dev/toolkits/scheduleonce/framework/openclaw) - [Hermes](https://composio.dev/toolkits/scheduleonce/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/scheduleonce/framework/cli) - [Google ADK](https://composio.dev/toolkits/scheduleonce/framework/google-adk) - [LangChain](https://composio.dev/toolkits/scheduleonce/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/scheduleonce/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/scheduleonce/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/scheduleonce/framework/crew-ai) ## Related Toolkits - [Google Calendar](https://composio.dev/toolkits/googlecalendar) - Google Calendar is a time management service for scheduling meetings, events, and reminders. It streamlines personal and team organization with integrated notifications and sharing options. - [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly. - [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place. - [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations. - [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals. - [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem. - [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity. - [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently. - [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place. - [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time. - [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time. - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools. - [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place. - [Apaleo](https://composio.dev/toolkits/apaleo) - Apaleo is a cloud-based property management platform for hospitality businesses. It centralizes reservations, billing, and daily operations for smoother hotel management. - [Appointo](https://composio.dev/toolkits/appointo) - Appointo is an appointment booking platform for Shopify stores. It lets businesses add online scheduling to their websites with zero coding. - [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place. - [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations. - [Bart](https://composio.dev/toolkits/bart) - Bart is the Bay Area Rapid Transit system, providing fast public transportation across the San Francisco Bay Area. It helps commuters and travelers get real-time schedule info, plan routes, and stay updated on service changes. - [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place. - [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Scheduleonce MCP? With a standalone Scheduleonce MCP server, the agents and LLMs can only access a fixed set of Scheduleonce tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Scheduleonce and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with LlamaIndex? Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Scheduleonce tools. ### Can I manage the permissions and scopes for Scheduleonce while using Tool Router? Yes, absolutely. You can configure which Scheduleonce scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Scheduleonce data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)