# How to integrate Eagle doc MCP with LangChain

```json
{
  "title": "How to integrate Eagle doc MCP with LangChain",
  "toolkit": "Eagle doc",
  "toolkit_slug": "eagle_doc",
  "framework": "LangChain",
  "framework_slug": "langchain",
  "url": "https://composio.dev/toolkits/eagle_doc/framework/langchain",
  "markdown_url": "https://composio.dev/toolkits/eagle_doc/framework/langchain.md",
  "updated_at": "2026-03-29T06:31:52.589Z"
}
```

## Introduction

This guide walks you through connecting Eagle doc to LangChain 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 LangChain 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)
- [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)
- [CrewAI](https://composio.dev/toolkits/eagle_doc/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Connect your Eagle doc project to Composio
- Create a Tool Router MCP session for Eagle doc
- Initialize an MCP client and retrieve Eagle doc tools
- Build a LangChain agent that can interact with Eagle doc
- Set up an interactive chat interface for testing

## What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.
Key features include:
- Agent Framework: Build agents that can use tools and make decisions
- MCP Integration: Connect to external services through Model Context Protocol adapters
- Memory Management: Maintain conversation history across interactions
- Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

## 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

No description provided.

### 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

No description provided.
```python
pip install composio-langchain langchain-mcp-adapters langchain python-dotenv
```

```typescript
npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv
```

### 3. Set up environment variables

Create a .env file in your project root.
What's happening:
- COMPOSIO_API_KEY authenticates your requests to Composio's API
- COMPOSIO_USER_ID identifies the user for session management
- OPENAI_API_KEY enables access to OpenAI's language models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import dependencies

No description provided.
```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

dotenv.config();
```

### 5. Initialize Composio client

What's happening:
- We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
- Creating a Composio instance that will manage our connection to Eagle doc tools
- Validating that COMPOSIO_USER_ID is also set before proceeding
```python
async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
```

```typescript
const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });
```

### 6. Create a Tool Router session

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 session.mcp.url is the MCP server URL that your agent will use
- This approach allows the agent to dynamically load and use Eagle doc tools as needed
```python
# Create Tool Router session for Eagle doc
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['eagle_doc']
)

url = session.mcp.url
```

```typescript
const session = await composio.create(
    userId as string,
    {
        toolkits: ['eagle_doc']
    }
);

const url = session.mcp.url;
```

### 7. Configure the agent with the MCP URL

No description provided.
```python
client = MultiServerMCPClient({
    "eagle_doc-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
```

```typescript
const client = new MultiServerMCPClient({
    "eagle_doc-agent": {
        transport: "http",
        url: url,
        headers: {
            "x-api-key": process.env.COMPOSIO_API_KEY
        }
    }
});

const tools = await client.getTools();

const agent = createAgent({ model: "gpt-5", tools });
```

### 8. Set up interactive chat interface

No description provided.
```python
conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Eagle doc related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
```

```typescript
let conversationHistory: any[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
console.log("Ask any Eagle doc related question or task to the agent.\n");

const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: '
});

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;
    }

    conversationHistory.push({ role: "user", content: trimmedInput });
    console.log("\nAgent is thinking...\n");

    const response = await agent.invoke({ messages: conversationHistory });
    conversationHistory = response.messages;

    const finalResponse = response.messages[response.messages.length - 1]?.content;
    console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\n👋 Session ended.');
        process.exit(0);
    });
```

### 9. Run the application

No description provided.
```python
if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Complete Code

```python
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['eagle_doc']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "eagle_doc-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Eagle doc related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

```typescript
import { Composio } from '@composio/core';
import { LangchainProvider } from '@composio/langchain';
import { MultiServerMCPClient } from "@langchain/mcp-adapters";  
import { createAgent } from "langchain";
import * as readline from 'readline';
import 'dotenv/config';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.COMPOSIO_USER_ID;

if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set');
if (!userId) throw new Error('COMPOSIO_USER_ID is not set');

async function main() {
    const composio = new Composio({
        apiKey: composioApiKey as string,
        provider: new LangchainProvider()
    });

    const session = await composio.create(
        userId as string,
        {
            toolkits: ['eagle_doc']
        }
    );

    const url = session.mcp.url;
    
    const client = new MultiServerMCPClient({
        "eagle_doc-agent": {
            transport: "http",
            url: url,
            headers: {
                "x-api-key": process.env.COMPOSIO_API_KEY
            }
        }
    });
    
    const tools = await client.getTools();
  
    const agent = createAgent({ model: "gpt-5", tools });
    
    let conversationHistory: any[] = [];
    
    console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n");
    console.log("Ask any Eagle doc related question or task to the agent.\n");
    
    const rl = readline.createInterface({
        input: process.stdin,
        output: process.stdout,
        prompt: 'You: '
    });

    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;
        }
        
        conversationHistory.push({ role: "user", content: trimmedInput });
        console.log("\nAgent is thinking...\n");
        
        const response = await agent.invoke({ messages: conversationHistory });
        conversationHistory = response.messages;
        
        const finalResponse = response.messages[response.messages.length - 1]?.content;
        console.log(`Agent: ${finalResponse}\n`);
        
        rl.prompt();
    });

    rl.on('close', () => {
        console.log('\nSession ended.');
        process.exit(0);
    });
}

main().catch((err) => {
    console.error('Fatal error:', err);
    process.exit(1);
});
```

## Conclusion

You've successfully built a LangChain agent that can interact with Eagle doc through Composio's Tool Router.
Key features of this implementation:
- Dynamic tool loading through Composio's Tool Router
- Conversation history maintenance for context-aware responses
- Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding 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)
- [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)
- [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 LangChain?

Yes, you can. LangChain 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)