# How to integrate Eagle doc MCP with CrewAI ```json { "title": "How to integrate Eagle doc MCP with CrewAI", "toolkit": "Eagle doc", "toolkit_slug": "eagle_doc", "framework": "CrewAI", "framework_slug": "crew-ai", "url": "https://composio.dev/toolkits/eagle_doc/framework/crew-ai", "markdown_url": "https://composio.dev/toolkits/eagle_doc/framework/crew-ai.md", "updated_at": "2026-03-29T06:31:52.589Z" } ``` ## Introduction This guide walks you through connecting Eagle doc to CrewAI 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 CrewAI 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) - [Vercel AI SDK](https://composio.dev/toolkits/eagle_doc/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/eagle_doc/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/eagle_doc/framework/llama-index) ## TL;DR Here's what you'll learn: - Get a Composio API key and configure your Eagle doc connection - Set up CrewAI with an MCP enabled agent - Create a Tool Router session or standalone MCP server for Eagle doc - Build a conversational loop where your agent can execute Eagle doc operations ## What is CrewAI? CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews. Key features include: - Agent Roles: Define specialized agents with specific goals and backstories - Task Management: Create tasks with clear descriptions and expected outputs - Crew Orchestration: Combine agents and tasks into collaborative workflows - MCP Integration: Connect to external tools through Model Context Protocol ## 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 starting, make sure you have: - Python 3.9 or higher - A Composio account and API key - A Eagle doc connection authorized in Composio - An OpenAI API key for the CrewAI LLM - Basic familiarity with Python ### 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 dependencies **What's happening:** - composio connects your agent to Eagle doc via MCP - crewai provides Agent, Task, Crew, and LLM primitives - crewai-tools[mcp] includes MCP helpers - python-dotenv loads environment variables from .env ```bash pip install composio crewai crewai-tools[mcp] python-dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates with Composio - USER_ID scopes the session to your account - OPENAI_API_KEY lets CrewAI use your chosen OpenAI model ```bash COMPOSIO_API_KEY=your_composio_api_key_here USER_ID=your_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies **What's happening:** - CrewAI classes define agents and tasks, and run the workflow - MCPServerHTTP connects the agent to an MCP endpoint - Composio will give you a short lived Eagle doc MCP URL ```python import os from composio import Composio from crewai import Agent, Task, Crew from crewai_tools import MCPServerAdapter import dotenv dotenv.load_dotenv() COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") 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") ``` ### 5. Create a Composio Tool Router session for Eagle doc **What's happening:** - You create a Eagle doc only session through Composio - Composio returns an MCP HTTP URL that exposes Eagle doc tools ```python composio_client = Composio(api_key=COMPOSIO_API_KEY) session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["eagle_doc"]) url = session.mcp.url ``` ### 6. Initialize the MCP Server **What's Happening:** - Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication. - MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format. - Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools. - Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops. - Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries. ```python server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users search the internet effectively", backstory="You are a helpful assistant with access to search tools.", tools=tools, verbose=False, max_iter=10, ) ``` ### 7. Create a CLI Chatloop and define the Crew **What's Happening:** - Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable. - Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean. - Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses. - Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context. - Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response. - Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity. ```python print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Complete Code ```python from crewai import Agent, Task, Crew, LLM from crewai_tools import MCPServerAdapter from composio import Composio from dotenv import load_dotenv import os load_dotenv() GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY") COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY") COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID") if not GOOGLE_API_KEY: raise ValueError("GOOGLE_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.") # Initialize Composio and create a session composio = Composio(api_key=COMPOSIO_API_KEY) session = composio.create( user_id=COMPOSIO_USER_ID, toolkits=["eagle_doc"], ) url = session.mcp.url # Configure LLM llm = LLM( model="gpt-5", api_key=os.getenv("OPENAI_API_KEY"), ) server_params = { "url": url, "transport": "streamable-http", "headers": {"x-api-key": COMPOSIO_API_KEY}, } with MCPServerAdapter(server_params) as tools: agent = Agent( role="Search Assistant", goal="Help users with internet searches", backstory="You are an expert assistant with access to Composio Search tools.", tools=tools, llm=llm, verbose=False, max_iter=10, ) print("Chat started! Type 'exit' or 'quit' to end.\n") conversation_context = "" while True: user_input = input("You: ").strip() if user_input.lower() in ["exit", "quit", "bye"]: print("\nGoodbye!") break if not user_input: continue conversation_context += f"\nUser: {user_input}\n" print("\nAgent is thinking...\n") task = Task( description=( f"Conversation history:\n{conversation_context}\n\n" f"Current request: {user_input}" ), expected_output="A helpful response addressing the user's request", agent=agent, ) crew = Crew(agents=[agent], tasks=[task], verbose=False) result = crew.kickoff() response = str(result) conversation_context += f"Agent: {response}\n" print(f"Agent: {response}\n") ``` ## Conclusion You now have a CrewAI agent connected to Eagle doc through Composio's Tool Router. The agent can perform Eagle doc operations through natural language commands. Next steps: - Add role-specific instructions to customize agent behavior - Plug in more toolkits for multi-app workflows - Chain tasks for complex multi-step operations ## 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) - [Vercel AI SDK](https://composio.dev/toolkits/eagle_doc/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/eagle_doc/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/eagle_doc/framework/llama-index) ## 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 CrewAI? Yes, you can. CrewAI 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)