# How to integrate Eagle doc MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Eagle doc MCP with Vercel AI SDK v6", "toolkit": "Eagle doc", "toolkit_slug": "eagle_doc", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/eagle_doc/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/eagle_doc/framework/ai-sdk.md", "updated_at": "2026-03-29T06:31:52.589Z" } ``` ## Introduction This guide walks you through connecting Eagle doc to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Eagle doc agent that can extract vendor name from uploaded invoice, summarize total expenses from receipt batch, list all line items from this receipt through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Eagle doc account through Composio's Eagle doc MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Eagle doc with - [OpenAI Agents SDK](https://composio.dev/toolkits/eagle_doc/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/eagle_doc/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/eagle_doc/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/eagle_doc/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/eagle_doc/framework/codex) - [OpenClaw](https://composio.dev/toolkits/eagle_doc/framework/openclaw) - [Hermes](https://composio.dev/toolkits/eagle_doc/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/eagle_doc/framework/cli) - [Google ADK](https://composio.dev/toolkits/eagle_doc/framework/google-adk) - [LangChain](https://composio.dev/toolkits/eagle_doc/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/eagle_doc/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/eagle_doc/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/eagle_doc/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Eagle doc integration - Using Composio's Tool Router to dynamically load and access Eagle doc 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 Eagle doc MCP server, and what's possible with it? The Eagle doc MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Eagle doc account. It provides structured and secure access so your agent can perform Eagle doc operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `EAGLE_DOC_ANY_DOC_OCR` | Process Any Document with OCR | Tool to process any document type with OCR and automatic classification. Supports bank statements, resumes, passports, delivery sheets, and more. Use when you need to extract structured data from various document types. | | `EAGLE_DOC_BATCH_ANY_DOC_OCR` | Submit Batch Any Document OCR Task | Tool to submit batch OCR processing tasks for various document types including bank statements, resumes, passports, delivery sheets, and more. Use when you need to asynchronously process documents with custom configurations. The task is processed asynchronously; use the Results Check API with the returned task ID to monitor status and retrieve results. | | `EAGLE_DOC_BATCH_TASK_DELETE` | Delete Batch Processing Task | Tool to delete a submitted batch processing task from the queue. Use when you need to cancel or remove a previously submitted batch OCR task before processing completes. | | `EAGLE_DOC_INVOICE_OCR_BASE64` | Eagle Doc Invoice OCR from Base64 | Tool to extract invoice data from base64 encoded images using Eagle Doc OCR API. Use when you need to process invoice images that are already base64 encoded. Supports optional parameters for privacy control, coordinate extraction, and full text extraction. | | `EAGLE_DOC_GET_MANAGEMENT_QUOTA` | Get Management Quota | Tool to get contractual quota allowance and current usage counters for all workloads. Use when you need to check remaining capacity for dashboards or billing workflows. | | `EAGLE_DOC_RECEIPT_OCR_V1_LEGACY` | Receipt OCR V1 (Legacy) | Tool to process receipt images with v1 API to extract structured data. Use when you need to extract merchant details, line items, totals, and payment information from receipt images or PDFs. Note: This is a deprecated legacy version; consider using newer API versions if available. | | `EAGLE_DOC_RECEIPT_OCR_V3` | Receipt OCR V3 | Tool to process receipt images into structured JSON with 40+ fields including merchant info, line items, taxes, and payments. Use when extracting detailed data from receipt images or PDFs. | | `EAGLE_DOC_GET_RECEIPT_QUOTA_V1` | Get Receipt Quota V1 | Tool to get quota information for receipt processing API v1 (deprecated). Use when you need to check remaining quota for receipt OCR processing. | | `EAGLE_DOC_GET_RECEIPT_QUOTA_V2_DEPRECATED` | Get Receipt Quota V2 (Deprecated) | Tool to get quota information for receipt processing API v2 (deprecated). Use when you need to check available quota and usage for receipt OCR processing. Note: Multi-page receipts count each page as one request. | | `EAGLE_DOC_EXTRACT_RESUME_INFORMATION` | Extract Resume Information | Tool to extract candidate information from resumes using OCR. Use when you need to parse resume documents and extract structured data including work experience, education, skills, certifications, and contact details. Supports PNG, JPG, TIF, and PDF formats. | | `EAGLE_DOC_GET_CURRENT_MONTH_USAGE` | Get Current Month Usage | Tool to get current month's usage statistics including quota, pages processed, over-usage, and costs. Use when you need to check API usage and billing information for the current billing period. | | `EAGLE_DOC_GET_MONTHLY_USAGE_HISTORY` | Get Monthly Usage History | Tool to retrieve historical monthly usage data with pricing context for reconciliation and forecasting. Use when you need to analyze page processing trends or calculate costs. | | `EAGLE_DOC_GET_USAGE_REQUEST_LOGS` | Get Usage Request Logs | Tool to retrieve chronological list of recent API calls with page counts and timestamps. Use for troubleshooting and auditing consumption patterns. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Eagle doc MCP server is an implementation of the Model Context Protocol that connects your AI agent to Eagle doc. It provides structured and secure access so your agent can perform Eagle doc 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 Eagle doc 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 Eagle doc-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: ["eagle_doc"], }); 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 Eagle doc 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 eagle_doc, 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 Eagle doc 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: ["eagle_doc"], }); 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 eagle_doc, 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 Eagle doc 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 Eagle doc MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/eagle_doc/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/eagle_doc/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/eagle_doc/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/eagle_doc/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/eagle_doc/framework/codex) - [OpenClaw](https://composio.dev/toolkits/eagle_doc/framework/openclaw) - [Hermes](https://composio.dev/toolkits/eagle_doc/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/eagle_doc/framework/cli) - [Google ADK](https://composio.dev/toolkits/eagle_doc/framework/google-adk) - [LangChain](https://composio.dev/toolkits/eagle_doc/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/eagle_doc/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/eagle_doc/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/eagle_doc/framework/crew-ai) ## Related Toolkits - [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices. - [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. - [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze. - [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization. - [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. - [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. - [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. - [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data. - [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. - [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease. - [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training. - [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. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Eagle doc MCP? With a standalone Eagle doc MCP server, the agents and LLMs can only access a fixed set of Eagle doc tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Eagle doc 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 Eagle doc tools. ### Can I manage the permissions and scopes for Eagle doc while using Tool Router? Yes, absolutely. You can configure which Eagle doc 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 Eagle doc data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)