# How to integrate Supportbee MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Supportbee MCP with Vercel AI SDK v6", "toolkit": "Supportbee", "toolkit_slug": "supportbee", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/supportbee/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/supportbee/framework/ai-sdk.md", "updated_at": "2026-05-12T10:27:33.636Z" } ``` ## Introduction This guide walks you through connecting Supportbee to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Supportbee agent that can archive all tickets resolved this week, assign new tickets to the support team, create a reusable snippet for refund replies through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Supportbee account through Composio's Supportbee MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Supportbee with - [OpenAI Agents SDK](https://composio.dev/toolkits/supportbee/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/supportbee/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/supportbee/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/supportbee/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/supportbee/framework/codex) - [OpenClaw](https://composio.dev/toolkits/supportbee/framework/openclaw) - [Hermes](https://composio.dev/toolkits/supportbee/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/supportbee/framework/cli) - [Google ADK](https://composio.dev/toolkits/supportbee/framework/google-adk) - [LangChain](https://composio.dev/toolkits/supportbee/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/supportbee/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/supportbee/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/supportbee/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Supportbee integration - Using Composio's Tool Router to dynamically load and access Supportbee tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the Supportbee MCP server, and what's possible with it? The Supportbee MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Supportbee account. It provides structured and secure access to your support ticketing system, so your agent can perform actions like creating and replying to tickets, managing team assignments, organizing tickets, and automating support workflows on your behalf. - Automated ticket creation and updates: Instantly open new support tickets, update their content, or post replies to customer inquiries without leaving your workflow. - Team assignment and ticket routing: Direct your agent to assign tickets to the right team or agent, ensuring every request is handled by the appropriate group. - Archiving and deleting tickets: Keep your helpdesk organized by having the agent archive resolved tickets or permanently remove unwanted ones from the system. - Reusable response snippets: Let your agent create, manage, and delete response templates so your team can reply faster and more consistently. - Rule-based workflow automation: Empower your agent to create new automation rules that streamline ticket routing, escalation, and handling based on custom conditions. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `SUPPORTBEE_ADD_LABEL_TO_TICKET` | Add Label to Ticket | Tool to add a label to a ticket. Use when you need to categorize or tag a ticket with a specific label. The label must already exist in your SupportBee account before adding it to a ticket. | | `SUPPORTBEE_ARCHIVE_TICKET` | Archive SupportBee Ticket | Tool to archive a SupportBee ticket by its ID. Use when you want to move resolved tickets to the archive. | | `SUPPORTBEE_ASSIGN_TICKET_TO_TEAM` | Assign Ticket to Team | Assigns a ticket to a team in SupportBee. Use when you need to route a support ticket to a specific team for handling. Note: If the ticket is already assigned to a team and a user, reassigning to another team will remove the user assignee. | | `SUPPORTBEE_CREATE_COMMENT` | Create Ticket Comment | Creates an internal comment on a ticket in SupportBee. Comments are private notes visible only to agents, not to customers. Use this to add internal notes, observations, or collaborate with team members on a ticket. | | `SUPPORTBEE_CREATE_CONSEQUENCE` | Create Consequence | Creates a new consequence for rules automation in SupportBee. Use when setting up automated actions that should be triggered by rules (e.g., auto-assign tickets, archive, or mark as spam). | | `SUPPORTBEE_CREATE_EMAIL` | Create Forwarding Email | Create a new forwarding email address for the company in SupportBee. Use this to add new support email addresses that will forward incoming emails to your SupportBee account as tickets. | | `SUPPORTBEE_CREATE_FILTER` | Create Filter | Creates a filter in SupportBee by linking a rule with a consequence. Use this after creating both a rule (defining match conditions) and a consequence (defining actions to perform). | | `SUPPORTBEE_CREATE_RULE` | Create Rule | Creates a new automation rule in SupportBee to automatically process tickets based on conditions. Rules allow you to automate ticket workflows by: - Matching tickets based on field conditions (subject, sender, body, etc.) - Automatically applying actions like labeling, archiving, assigning, or setting priority Use this after fetching available labels/teams to get valid IDs for actions. The rule will be evaluated for all new and existing tickets matching the conditions. Returns the created rule's unique ID. | | `SUPPORTBEE_CREATE_SNIPPET` | Create Snippet | Create a reusable snippet (canned response) in SupportBee. Snippets are pre-written text templates that agents can quickly insert into ticket replies. Use this to create standard responses for common customer inquiries like refunds, FAQs, or welcome messages. | | `SUPPORTBEE_CREATE_TICKET` | Create SupportBee Ticket | Creates a new support ticket in SupportBee with a subject, content, and requester details. Use this action to: - Create tickets from customer inquiries or issues - Assign tickets to specific agents or teams during creation - Add tags and labels for better ticket organization - Include CC recipients to keep stakeholders informed The ticket will be created in an unanswered state and will appear in the inbox unless marked as spam. | | `SUPPORTBEE_CREATE_TICKET_REPLY` | Create Ticket Reply | Create a reply to a support ticket in SupportBee. Replies are sent to customers via email and are visible to them. Use this when you need to respond to a customer's ticket with information, updates, or solutions. Provide the ticket ID and HTML-formatted content for your reply. | | `SUPPORTBEE_CREATE_USER_OR_CUSTOMER_GROUP` | Create SupportBee User | Invites a new user to your SupportBee account. The user will receive an email invitation and can be assigned as an agent (handles tickets), admin (full access), or collaborator (view/comment only). Use this when you need to add team members to your helpdesk programmatically. | | `SUPPORTBEE_DELETE_SNIPPET` | Delete Snippet | Permanently delete a snippet by its ID from SupportBee. Use this action when you need to remove an unwanted or outdated snippet (canned response template). This action is destructive and cannot be undone. To find snippet IDs, use the 'Fetch Snippets' action first. | | `SUPPORTBEE_DELETE_TICKET` | Delete SupportBee Ticket | Permanently delete a trashed ticket from SupportBee. The ticket must first be moved to trash using the Trash Ticket action before it can be permanently deleted. Only admins can delete trashed tickets. This action is irreversible. | | `SUPPORTBEE_FETCH_EMAILS` | Fetch Forwarding Emails | Retrieve all forwarding email addresses configured for the company. Use this tool to list the support email addresses that forward emails to SupportBee. | | `SUPPORTBEE_FETCH_LABELS` | Fetch SupportBee Labels | Tool to retrieve all custom labels. Use when you need to list labels for ticket categorization. | | `SUPPORTBEE_FETCH_SNIPPETS` | Fetch Snippets | Fetches saved response snippets (canned responses/templates) from SupportBee. Snippets are reusable text templates that can be inserted into ticket replies. Use this to list available snippets for quick responses. | | `SUPPORTBEE_FETCH_TEAMS` | Fetch SupportBee Teams | Retrieves all teams in the SupportBee account. Use this to list available teams before assigning tickets to teams or filtering tickets by team. Returns team IDs, names, descriptions, and timestamps. | | `SUPPORTBEE_GET_AVG_FIRST_RESPONSE_TIME_REPORT` | Get Avg First Response Time Report | Tool to retrieve average first response time data points over time. Use when analyzing first-response performance metrics for support tickets. Returns time-series data with response times in seconds and Unix timestamps. Reports require admin API token access. Data is limited to a maximum 30-day window per request. | | `SUPPORTBEE_GET_REPLIES_COUNT_REPORT` | Get Replies Count Report | Retrieves replies count report data for the company. Returns time-series data points showing the number of replies over time. The report provides aggregate metrics for the entire company account and includes type information (company/user/team), the entity ID, and the metric name. Requires admin-level API access. Use this to analyze reply volume trends and patterns. | | `SUPPORTBEE_GET_TICKET` | Get Ticket | Tool to retrieve a specific SupportBee ticket by its ID. Returns complete ticket details including subject, content, requester, assignee, labels, and reply/comment counts. Use when you need to fetch full details of a single ticket. | | `SUPPORTBEE_GET_TICKETS_COUNT_REPORT` | Get Tickets Count Report | Tool to get ticket count data points over time. Use when analyzing ticket volume trends within a specific date range. Supports optional filtering by agent, team, or label. | | `SUPPORTBEE_LIST_TICKET_COMMENTS` | List Ticket Comments | Retrieves all internal comments (private agent notes) for a specific ticket. Comments are visible only to agents within the helpdesk, not to customers. Use this to review internal discussion history on a ticket. | | `SUPPORTBEE_LIST_TICKET_REPLIES` | List Ticket Replies | Lists all replies on a specific support ticket in SupportBee. Returns reply content, replier details, timestamps, and attachments. Use this to view the conversation history on a ticket. Returns an empty list if the ticket has no replies yet. | | `SUPPORTBEE_LIST_TICKETS` | List Tickets | Tool to list tickets from SupportBee. Returns a paginated list of tickets with optional filters for spam, trash, archived, assigned user/group, labels, and more. Use when you need to retrieve and browse tickets in the helpdesk. | | `SUPPORTBEE_LIST_USERS` | List SupportBee Users | Retrieves all users and customer groups in your SupportBee company. Use this when you need to list team members, filter by user type (agents/admins vs customer groups), or include invited users who haven't confirmed their accounts yet. | | `SUPPORTBEE_MARK_TICKET_AS_ANSWERED` | Mark SupportBee Ticket as Answered | Marks a SupportBee ticket as answered by adding the 'answered' status. Use this after sending a response to a customer to indicate the ticket has been addressed. This action is idempotent - calling it on an already answered ticket has no adverse effect. | | `SUPPORTBEE_MARK_TICKET_AS_SPAM` | Mark SupportBee Ticket as Spam | Tool to mark a SupportBee ticket as spam. Use when you need to flag unwanted or malicious ticket submissions after obtaining the ticket ID. | | `SUPPORTBEE_MARK_TICKET_AS_UNANSWERED` | Mark SupportBee Ticket as Unanswered | Marks a SupportBee ticket as unanswered by removing its 'answered' status. Use this to revert a ticket's status after it was previously marked as answered, typically when additional follow-up is needed from the support team. This action is idempotent - calling it on an already unanswered ticket has no adverse effect. | | `SUPPORTBEE_REMOVE_LABEL_FROM_TICKET` | Remove Label From Ticket | Tool to remove a label from a ticket. Use when you need to unlabel or uncategorize a ticket by removing an existing label. | | `SUPPORTBEE_SEARCH_TICKETS` | Search SupportBee Tickets | Tool to search SupportBee tickets. Use when you need to find tickets by query with pagination. | | `SUPPORTBEE_SHOW_TICKET_REPLY` | Show Ticket Reply | Tool to fetch a specific reply for a SupportBee ticket. Use when you need details of a single reply by ticket and reply IDs. | | `SUPPORTBEE_SHOW_USER_OR_CUSTOMER_GROUP` | Show SupportBee User or Customer Group | Retrieves details of a SupportBee user (agent/admin) or customer group by their ID. Use this action when you need to fetch profile information like name, email, role, or timestamps for a specific user whose ID you already have (e.g., from a ticket response). | | `SUPPORTBEE_TRASH_TICKET` | Trash SupportBee Ticket | Tool to trash a SupportBee ticket by its ID. Use when you need to remove a ticket into the trash folder. | | `SUPPORTBEE_UNARCHIVE_TICKET` | Unarchive SupportBee Ticket | Tool to unarchive a SupportBee ticket by its ID. Use when you need to restore an archived ticket back to active status. | | `SUPPORTBEE_UNASSIGN_TICKET_FROM_TEAM` | Unassign Ticket from Team | Tool to un-assign a ticket from its assigned team. Use when you need to remove the current team ownership before reassigning or closing the ticket. | | `SUPPORTBEE_UNASSIGN_TICKET_FROM_USER` | Unassign User From Ticket | Tool to un-assign a ticket from its assigned user/agent. Use when you need to remove the current user ownership before reassigning to a different user or closing the ticket. | | `SUPPORTBEE_UNMARK_TICKET_AS_SPAM` | Unmark SupportBee Ticket as Spam | Tool to unmark a SupportBee ticket as spam. Use when a ticket was incorrectly flagged as spam. | | `SUPPORTBEE_UNTRASH_TICKET` | Untrash SupportBee Ticket | Restores a trashed SupportBee ticket back to active status. Use when you need to recover a ticket that was previously moved to trash. | | `SUPPORTBEE_UPDATE_SNIPPET` | Update Snippet | Update an existing snippet (canned response) in SupportBee. Use this to modify the name, content, or tags of a snippet. To find snippet IDs, use the 'Fetch Snippets' action first. | | `SUPPORTBEE_UPDATE_USER` | Update SupportBee User | Update an existing SupportBee user's profile information including name, email, role, avatar, or signature. This action modifies user account details via the SupportBee API. You can update one or multiple fields in a single request. Commonly used to change user roles (agent/admin), update contact information, or customize user profiles. Requirements: - Valid user ID (obtain from SUPPORTBEE_CREATE_USER_OR_CUSTOMER_GROUP or other user-related actions) - At least one field to update (name, email, role, avatar_url, or signature) Common use cases: - Promote an agent to admin by updating the role field - Update user email addresses when they change - Customize user signatures for support ticket replies | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Supportbee MCP server is an implementation of the Model Context Protocol that connects your AI agent to Supportbee. It provides structured and secure access so your agent can perform Supportbee 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: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Supportbee tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Supportbee-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["supportbee"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Supportbee tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to supportbee, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Supportbee tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["supportbee"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to supportbee, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n👋 Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Supportbee agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Supportbee MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/supportbee/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/supportbee/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/supportbee/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/supportbee/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/supportbee/framework/codex) - [OpenClaw](https://composio.dev/toolkits/supportbee/framework/openclaw) - [Hermes](https://composio.dev/toolkits/supportbee/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/supportbee/framework/cli) - [Google ADK](https://composio.dev/toolkits/supportbee/framework/google-adk) - [LangChain](https://composio.dev/toolkits/supportbee/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/supportbee/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/supportbee/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/supportbee/framework/crew-ai) ## Related Toolkits - [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. 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It helps businesses automate support and streamline interactions through natural, voice-powered conversations. - [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code. - [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding. - [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls. - [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources. - [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates. - [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly. - [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time. - [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows. - [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment. - [Docsbot ai](https://composio.dev/toolkits/docsbot_ai) - Docsbot ai is a platform that lets you build custom AI chatbots trained on your documentation. It automates customer support and content generation, saving time and improving response quality. - [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster. - [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment. - [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support. - [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach. - [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Supportbee MCP? With a standalone Supportbee MCP server, the agents and LLMs can only access a fixed set of Supportbee tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Supportbee and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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 Supportbee tools. ### Can I manage the permissions and scopes for Supportbee while using Tool Router? Yes, absolutely. You can configure which Supportbee 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 Supportbee data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)