# How to integrate Givebutter MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Givebutter MCP with Vercel AI SDK v6", "toolkit": "Givebutter", "toolkit_slug": "givebutter", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/givebutter/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/givebutter/framework/ai-sdk.md", "updated_at": "2026-05-06T08:13:30.553Z" } ``` ## Introduction This guide walks you through connecting Givebutter to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Givebutter agent that can create a new fundraising campaign for our school, list all recent payouts to our nonprofit account, get details for fund with id fund_abc123 through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Givebutter account through Composio's Givebutter MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Givebutter with - [OpenAI Agents SDK](https://composio.dev/toolkits/givebutter/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/givebutter/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/givebutter/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/givebutter/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/givebutter/framework/codex) - [OpenClaw](https://composio.dev/toolkits/givebutter/framework/openclaw) - [Hermes](https://composio.dev/toolkits/givebutter/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/givebutter/framework/cli) - [Google ADK](https://composio.dev/toolkits/givebutter/framework/google-adk) - [LangChain](https://composio.dev/toolkits/givebutter/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/givebutter/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/givebutter/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/givebutter/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Givebutter integration - Using Composio's Tool Router to dynamically load and access Givebutter 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 Givebutter MCP server, and what's possible with it? The Givebutter MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Givebutter account. It provides structured and secure access to your fundraising platform, so your agent can perform actions like creating campaigns, tracking donations, managing contacts, and handling payouts on your behalf. - Campaign management and creation: Easily instruct your agent to start new fundraising campaigns, update campaign details, or remove old campaigns when needed. - Donation and payout tracking: Ask your agent to retrieve lists of payouts, monitor donation flows, and keep tabs on your fundraising progress in real time. - Contact and member administration: Let your agent add, archive, or delete contacts, and fetch lists of campaign members for smooth supporter management. - Fund and webhook operations: Direct your agent to get details about specific funds, create or remove webhooks for event notifications, and manage fundraising infrastructure automatically. - Automated data cleanup: Empower your agent to archive or delete obsolete contacts, funds, or webhooks, keeping your Givebutter account organized and up to date. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `GIVEBUTTER_ARCHIVE_CONTACT` | Archive Contact | Tool to archive a contact by their id. use after ensuring the contact has no associated data (e.g., no transactions or communications). example: "archive contact abc123". | | `GIVEBUTTER_CREATE_CAMPAIGN` | Create Campaign | Tool to create a new campaign. use when you have title, description, goal, and type ready, after confirming your givebutter account is authenticated. | | `GIVEBUTTER_CREATE_WEBHOOK` | Create Webhook | Tool to create a new webhook subscription. use when you need to receive real-time notifications programmatically after confirming your endpoint can validate givebutter's signing secret. | | `GIVEBUTTER_DELETE_CAMPAIGN` | Delete Campaign | Tool to delete a campaign by its id. use after confirming the campaign has no funds raised. example: "delete campaign abc123". | | `GIVEBUTTER_DELETE_CONTACT` | Delete Contact | Tool to delete a contact by their id. use after confirming the contact has no associated data (e.g., no transactions or communications). example: "delete contact abc123". | | `GIVEBUTTER_DELETE_FUND` | Delete Fund | Tool to delete a fund by its id. use when you need to remove a fund after confirming it exists. example: "delete fund fund abc123". | | `GIVEBUTTER_DELETE_WEBHOOK` | Delete Webhook | Tool to delete a webhook by its id. use when you need to remove an obsolete webhook after confirming no further events are needed. example: "delete webhook abc123". | | `GIVEBUTTER_GET_FUND` | Get Fund | Tool to retrieve details of a specific fund by its id. use after confirming the fund id is valid. | | `GIVEBUTTER_GET_MEMBERS` | Get Members | Tool to retrieve a paginated list of members for a given campaign. use when you need to list or process campaign members. | | `GIVEBUTTER_GET_PAYOUTS` | Get Payouts | Tool to retrieve a list of payouts associated with your account. use when you need to list withdrawal transactions after authentication. | | `GIVEBUTTER_GET_PLANS` | Get Plans | Tool to retrieve a list of plans associated with your account. use after authentication to fetch recurring donation plans. | | `GIVEBUTTER_GET_TEAMS` | Get Teams | Tool to retrieve a list of teams for a specific campaign. use after creating or updating a campaign when you need to list fundraising teams. example: "get teams for campaign camp123". | | `GIVEBUTTER_GET_TICKETS` | Get Tickets | Tool to retrieve a list of tickets. use when you need to list all tickets for your account after authentication. | | `GIVEBUTTER_GET_TRANSACTIONS` | Get Transactions | Tool to retrieve a list of transactions associated with your account. use when you need to list all donations and payments, optionally filtered by scope. | | `GIVEBUTTER_GET_WEBHOOKS` | Get Webhooks | Tool to retrieve all webhooks configured for your account. use after obtaining valid authentication. | | `GIVEBUTTER_UPDATE_CAMPAIGN` | Update Campaign | Tool to update an existing campaign's details by its id. use when you need to modify campaign attributes after creation. | | `GIVEBUTTER_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact's details by contact id. use when modifying contact information after confirming the contact id. only provided fields will be updated. | | `GIVEBUTTER_UPDATE_WEBHOOK` | Update Webhook | Tool to update an existing webhook subscription's details. use when you need to modify a webhook's name, url, trigger events, or enabled state after confirming its id. example: "update webhook wh 1234567890 to point to https://example.com/hook, enable transaction.succeeded only." | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Givebutter MCP server is an implementation of the Model Context Protocol that connects your AI agent to Givebutter. It provides structured and secure access so your agent can perform Givebutter 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 Givebutter 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 Givebutter-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: ["givebutter"], }); 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 Givebutter 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 givebutter, 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 Givebutter 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("\n๐Ÿ‘‹ 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: ["givebutter"], }); 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 givebutter, 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("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Givebutter 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 Givebutter MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/givebutter/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/givebutter/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/givebutter/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/givebutter/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/givebutter/framework/codex) - [OpenClaw](https://composio.dev/toolkits/givebutter/framework/openclaw) - [Hermes](https://composio.dev/toolkits/givebutter/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/givebutter/framework/cli) - [Google ADK](https://composio.dev/toolkits/givebutter/framework/google-adk) - [LangChain](https://composio.dev/toolkits/givebutter/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/givebutter/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/givebutter/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/givebutter/framework/crew-ai) ## Related Toolkits - [Stripe](https://composio.dev/toolkits/stripe) - Stripe is a global online payments platform offering APIs for managing payments, customers, and subscriptions. Trusted by businesses for secure, efficient, and scalable payment processing worldwide. - [Alpha vantage](https://composio.dev/toolkits/alpha_vantage) - Alpha Vantage is a financial data platform offering real-time and historical stock market APIs. Get instant, reliable access to equities, forex, and technical analysis data for smarter trading decisions. - [Altoviz](https://composio.dev/toolkits/altoviz) - Altoviz is a cloud-based billing and invoicing platform for businesses. It streamlines online payments, expense tracking, and customizable invoice management. - [Benzinga](https://composio.dev/toolkits/benzinga) - Benzinga provides real-time financial news and data APIs for market coverage. It helps you track breaking news and actionable market insights instantly. - [Brex](https://composio.dev/toolkits/brex) - Brex provides corporate credit cards and spend management tailored for startups and tech businesses. It helps optimize company cash flow, streamline accounting, and accelerate business growth. - [Chaser](https://composio.dev/toolkits/chaser) - Chaser is accounts receivable automation software that sends invoice reminders and helps businesses get paid faster. It streamlines the collections process to save time and improve cash flow. - [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. - [Coinbase](https://composio.dev/toolkits/coinbase) - Coinbase is a platform for buying, selling, and storing cryptocurrency. It makes exchanging and managing crypto simple and secure for everyone. - [Coinranking](https://composio.dev/toolkits/coinranking) - Coinranking is a comprehensive cryptocurrency market data platform offering access to real-time coin prices, market caps, and historical data. Get accurate, up-to-date stats for thousands of digital assets in one place. - [Coupa](https://composio.dev/toolkits/coupa) - Coupa is a business spend management platform for procurement, invoicing, and expenses. It helps organizations streamline purchasing, control costs, and gain complete visibility over financial operations. - [CurrencyScoop](https://composio.dev/toolkits/currencyscoop) - CurrencyScoop is a developer-friendly API for real-time and historical currency exchange rates. Easily access fiat and crypto data for smart, up-to-date financial applications. - [Daffy](https://composio.dev/toolkits/daffy) - Daffy is a modern charitable giving platform with a donor-advised fund. Easily set aside funds, grow them tax-free, and donate to over 1.7 million U.S. charities. - [Eagle doc](https://composio.dev/toolkits/eagle_doc) - Eagle doc is an AI-powered OCR API for invoices and receipts. It delivers fast, reliable, and accurate document data extraction for seamless automation. - [Elorus](https://composio.dev/toolkits/elorus) - Elorus is an online invoicing and time-tracking software for freelancers and small businesses. Easily manage finances, bill clients, and track work in one place. - [Eodhd apis](https://composio.dev/toolkits/eodhd_apis) - Eodhd apis delivers comprehensive financial data, including live and historical stock prices, via robust APIs. Easily access reliable, up-to-date market insights to power your apps, dashboards, and analytics. - [Fidel api](https://composio.dev/toolkits/fidel_api) - Fidel api is a secure platform for linking payment cards to web and mobile apps. It enables real-time card transaction monitoring and event-based automation for businesses. - [Finage](https://composio.dev/toolkits/finage) - Finage is a secure API platform delivering real-time and historical financial data for stocks, forex, crypto, indices, and commodities. It empowers developers and businesses to access, analyze, and act on market data instantly. - [Finmei](https://composio.dev/toolkits/finmei) - Finmei is an invoicing tool that simplifies billing, invoice management, and expense tracking. Ideal for automating and organizing your business finances in one place. - [Fixer](https://composio.dev/toolkits/fixer) - Fixer is a currency data API offering real-time and historical exchange rates for 170 currencies. Instantly access accurate, up-to-date forex data for your applications and workflows. - [Fixer io](https://composio.dev/toolkits/fixer_io) - Fixer.io is a lightweight API for real-time and historical foreign exchange rates. It makes global currency conversion fast, accurate, and hassle-free. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Givebutter MCP? With a standalone Givebutter MCP server, the agents and LLMs can only access a fixed set of Givebutter tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Givebutter 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 Givebutter tools. ### Can I manage the permissions and scopes for Givebutter while using Tool Router? Yes, absolutely. You can configure which Givebutter 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 Givebutter data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)