# How to integrate Taggun MCP with Google ADK

```json
{
  "title": "How to integrate Taggun MCP with Google ADK",
  "toolkit": "Taggun",
  "toolkit_slug": "taggun",
  "framework": "Google ADK",
  "framework_slug": "google-adk",
  "url": "https://composio.dev/toolkits/taggun/framework/google-adk",
  "markdown_url": "https://composio.dev/toolkits/taggun/framework/google-adk.md",
  "updated_at": "2026-05-12T10:27:48.117Z"
}
```

## Introduction

This guide walks you through connecting Taggun to Google ADK using the Composio tool router. By the end, you'll have a working Taggun agent that can extract vendor and total from this receipt image url, list all line items from uploaded invoice link, validate this receipt url before submitting expense through natural language commands.
This guide will help you understand how to give your Google ADK agent real control over a Taggun account through Composio's Taggun MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Taggun with

- [OpenAI Agents SDK](https://composio.dev/toolkits/taggun/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/taggun/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/taggun/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/taggun/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/taggun/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/taggun/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/taggun/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/taggun/framework/cli)
- [LangChain](https://composio.dev/toolkits/taggun/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/taggun/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/taggun/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/taggun/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/taggun/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get a Taggun account set up and connected to Composio
- Install the Google ADK and Composio packages
- Create a Composio Tool Router session for Taggun
- Build an agent that connects to Taggun through MCP
- Interact with Taggun using natural language

## What is Google ADK?

Google ADK (Agents Development Kit) is Google's framework for building AI agents powered by Gemini models. It provides tools for creating agents that can use external services through the Model Context Protocol.
Key features include:
- Gemini Integration: Native support for Google's Gemini models
- MCP Toolset: Built-in support for Model Context Protocol tools
- Streamable HTTP: Connect to external services through streamable HTTP
- CLI and Web UI: Run agents via command line or web interface

## What is the Taggun MCP server, and what's possible with it?

The Taggun MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Taggun account. It provides structured and secure access to real-time receipt OCR and merchant management, so your agent can scan receipts, extract detailed data, validate image URLs, and manage merchant records on your behalf.
- Instant receipt data extraction: Have your agent process receipt or invoice images via public URLs to pull out structured purchase data quickly and accurately.
- Detailed line item analysis: Use verbose extraction to get comprehensive data including line items, merchant info, and confidence metrics from receipt images or PDFs.
- Automated merchant registry management: Export the full list of known merchants for audits or synchronize merchant data directly through your agent.
- Receipt image URL validation: Let your agent check if a receipt image URL meets campaign and validation requirements before processing.
- Generate merchant mock CSVs for testing: Easily create sample merchant CSV files to test or bulk import merchant data as part of your automation workflow.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `TAGGUN_ADD_MERCHANT_NAME` | Add Merchant Name | Tool to add a merchant name keyword to your account's model for predicting merchant names. Use when you want to improve merchant name recognition by training the model with specific merchant names. Changes to your account's model are updated daily and will affect future receipt processing. |
| `TAGGUN_EXPORT_KNOWN_MERCHANTS` | Export Known Merchants | Export the complete list of known merchants used for merchant name normalization in Taggun. Returns CSV data with merchant details including location IDs, names, addresses, and coordinates. Use this when you need to retrieve the full merchant registry for synchronization, auditing, or analysis. No parameters required - this is a read-only GET operation. |
| `TAGGUN_EXPORT_KNOWN_PRODUCT_CODES` | Export Known Product Codes | Export the complete list of known product codes used for product normalization and matching in Taggun. Returns CSV data with product code information. Use this when you need to retrieve the full product code registry for synchronization, auditing, or analysis. No parameters required - this is a read-only GET operation. |
| `TAGGUN_EXPORT_PRODUCT_CATEGORIES` | Export Product Categories | Export a list of product categories and descriptions used for product categorization in CSV format. Returns CSV data with product category information for analysis or synchronization purposes. Use this when you need to retrieve the complete product category registry. |
| `TAGGUN_GENERATE_MERCHANTS_CSV` | Generate Merchants CSV | Generate a CSV file with mock merchant data for testing purposes. Creates a temporary CSV file with the specified number of merchant rows, including fields like name, alias, address, coordinates, contact info, and tags. Use this when you need sample merchant data for bulk import operations or testing merchant-related API endpoints. The generated CSV follows a standard format with 10 columns: name, alias, address, postcode, lat, lng, country, phone, email, tags. |
| `TAGGUN_IMPORT_KNOWN_MERCHANTS` | Import Known Merchants | Import a list of merchant names and addresses to normalize and match in CSV or TSV format. Use this when you need to bulk upload merchant data for name normalization and matching. File must be less than 20MB and contain merchant information in CSV or TSV format. |
| `TAGGUN_IMPORT_KNOWN_PRODUCT_CODES` | Import Known Product Codes | Tool to import a list of product codes in CSV or TSV format for normalization and matching. Use when you need to upload product code data to Taggun for receipt/invoice processing. The file should contain product codes with descriptions (e.g., code,description columns). |
| `TAGGUN_IMPORT_PRODUCT_CATEGORIES` | Import Product Categories | Import a list of product categories and descriptions for product categorization. Accepts CSV or TSV files (less than 20MB) with category and description columns. Use this when you need to bulk import product category data for matching during receipt processing. |
| `TAGGUN_TRANSCRIBE_RECEIPT_ENCODED_SIMPLE` | Transcribe Receipt from Base64 Encoded Image | Extract structured data from a receipt or invoice using base64 encoded image data. Provide a base64 encoded image (JPEG, PNG, PDF, GIF) along with filename and content type to get back extracted fields like total amount, date, merchant name, tax, line items, and confidence scores. Use this when you have receipt/invoice image data already encoded as base64 and need to digitize the data. The API uses machine learning OCR to detect and extract key fields automatically. |
| `TAGGUN_TRANSCRIBE_RECEIPT_ENCODED_VERBOSE` | Transcribe Receipt Encoded Verbose | Tool to transcribe a receipt using base64 encoded image in JSON payload and return detailed results. Use when you have a base64 encoded receipt image and require comprehensive output including line items, merchant details, and confidence levels. The image must be larger than 1x1 pixels to avoid validation errors. |
| `TAGGUN_TRANSCRIBE_RECEIPT_FILE_SIMPLE` | Transcribe Receipt File (Simple) | Tool to upload a receipt or invoice image file and extract basic data including merchant name, total amount, tax amount, and date. Use when you need to digitize receipt data from a file (PDF, JPG, PNG, GIF, HEIC up to 20MB). The API uses OCR to detect and extract key fields. |
| `TAGGUN_URL` | Process Receipt via URL | Extract structured data from a receipt or invoice image using OCR. Provide a public URL to a receipt/invoice image (JPEG, PNG, PDF, GIF) and get back extracted fields like total amount, date, merchant name, tax, line items, and confidence scores. Use this when you need to digitize receipt/invoice data from a publicly accessible image URL. The API uses machine learning OCR to detect and extract key fields automatically. |
| `TAGGUN_URL_VALIDATION` | URL Validation | Tool to extract and validate receipt data from a URL. Processes a receipt image from a public URL and returns extracted fields with confidence levels to assess receipt authenticity. Use when you have a receipt URL and need to verify it contains valid receipt data. |
| `TAGGUN_URL_VERBOSE` | URL Verbose | Tool to process a receipt or invoice from a URL for detailed data extraction. Use when you have a publicly accessible receipt or invoice URL and require comprehensive output including line items, merchant details, and confidence metrics. Call after verifying the URL is reachable. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Taggun MCP server is an implementation of the Model Context Protocol that connects your AI agent to Taggun. It provides structured and secure access so your agent can perform Taggun 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:
- A Google API key for Gemini models
- A Composio account and API key
- Python 3.9 or later installed
- Basic familiarity with Python

### 1. Getting API Keys for Google and Composio

Google API Key
- Go to [Google AI Studio](https://aistudio.google.com/app/apikey) and create an API key.
- Copy the key and keep it safe. You will put this in GOOGLE_API_KEY.
Composio API Key and User ID
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings → API Keys and copy your Composio API key. Use this for COMPOSIO_API_KEY.
- Decide on a stable user identifier to scope sessions, often your email or a user ID. Use this for COMPOSIO_USER_ID.

### 2. Install dependencies

Inside your virtual environment, install the required packages.
What's happening:
- google-adk is Google's Agents Development Kit
- composio connects your agent to Taggun via MCP
- python-dotenv loads environment variables
```bash
pip install google-adk composio python-dotenv
```

### 3. Set up ADK project

Set up a new Google ADK project.
What's happening:
- This creates an agent folder with a root agent file and .env file
```bash
adk create my_agent
```

### 4. Set environment variables

Save all your credentials in the .env file.
What's happening:
- GOOGLE_API_KEY authenticates with Google's Gemini models
- COMPOSIO_API_KEY authenticates with Composio
- COMPOSIO_USER_ID identifies the user for session management
```bash
GOOGLE_API_KEY=your-google-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id-or-email
```

### 5. Import modules and validate environment

What's happening:
- os reads environment variables
- Composio is the main Composio SDK client
- GoogleProvider declares that you are using Google ADK as the agent runtime
- Agent is the Google ADK LLM agent class
- McpToolset lets the ADK agent call MCP tools over HTTP
```python
import os
import warnings

from composio import Composio
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()

warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

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.")
```

### 6. Create Composio client and Tool Router session

What's happening:
- Authenticates to Composio with your API key
- Declares Google ADK as the provider
- Spins up a short-lived MCP endpoint for your user and selected toolkit
- Stores the MCP HTTP URL for the ADK MCP integration
```python
composio_client = Composio(api_key=COMPOSIO_API_KEY)

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["taggun"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url,
print(f"Composio MCP URL: {COMPOSIO_MCP_URL}")
```

### 7. Set up the McpToolset and create the Agent

What's happening:
- Connects the ADK agent to the Composio MCP endpoint through McpToolset
- Uses Gemini as the model powering the agent
- Lists exact tool names in instruction to reduce misnamed tool calls
```python
composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Taggun operations."
    ),
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
```

### 8. Run the agent

Execute the agent from the project root. The web command opens a web portal where you can chat with the agent.
What's happening:
- adk run runs the agent in CLI mode
- adk web . opens a web UI for interactive testing
```bash
# Run in CLI mode
adk run my_agent

# Or run in web UI mode
adk web
```

## Complete Code

```python
import os
import warnings

from composio import Composio
from composio_google import GoogleProvider
from dotenv import load_dotenv
from google.adk.agents.llm_agent import Agent
from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset

load_dotenv()
warnings.filterwarnings("ignore", message=".*BaseAuthenticatedTool.*")

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.")

composio_client = Composio(api_key=COMPOSIO_API_KEY, provider=GoogleProvider())

composio_session = composio_client.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["taggun"],
)

COMPOSIO_MCP_URL = composio_session.mcp.url


composio_toolset = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url=COMPOSIO_MCP_URL,
        headers={"x-api-key": COMPOSIO_API_KEY}
    )
)

root_agent = Agent(
    model="gemini-2.5-flash",
    name="composio_agent",
    description="An agent that uses Composio tools to perform actions.",
    instruction=(
        "You are a helpful assistant connected to Composio. "
        "You have the following tools available: "
        "COMPOSIO_SEARCH_TOOLS, COMPOSIO_MULTI_EXECUTE_TOOL, "
        "COMPOSIO_MANAGE_CONNECTIONS, COMPOSIO_REMOTE_BASH_TOOL, COMPOSIO_REMOTE_WORKBENCH. "
        "Use these tools to help users with Taggun operations."
    ),  
    tools=[composio_toolset],
)

print("\nAgent setup complete. You can now run this agent directly ;)")
```

## Conclusion

You've successfully integrated Taggun with the Google ADK through Composio's MCP Tool Router. Your agent can now interact with Taggun using natural language commands.
Key takeaways:
- The Tool Router approach dynamically routes requests to the appropriate Taggun tools
- Environment variables keep your credentials secure and separate from code
- Clear agent instructions reduce tool calling errors
- The ADK web UI provides an interactive interface for testing and development
You can extend this setup by adding more toolkits to the toolkits array in your session configuration.

## How to build Taggun MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/taggun/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/taggun/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/taggun/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/taggun/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/taggun/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/taggun/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/taggun/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/taggun/framework/cli)
- [LangChain](https://composio.dev/toolkits/taggun/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/taggun/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/taggun/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/taggun/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/taggun/framework/crew-ai)

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- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
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- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Taggun MCP?

With a standalone Taggun MCP server, the agents and LLMs can only access a fixed set of Taggun tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Taggun and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Google ADK?

Yes, you can. Google ADK 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 Taggun tools.

### Can I manage the permissions and scopes for Taggun while using Tool Router?

Yes, absolutely. You can configure which Taggun 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 Taggun data and credentials are handled as safely as possible.

---
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