# Pub/Sub Subscription MCP

> Google Pub/Sub Subscription MCP lets your AI client act as a dedicated, secure background worker for one specific message queue. It pulls messages from a single Google Pub/Sub subscription and confirms completion. This setup is perfect for building automated systems that process incoming tasks reliably without needing global cloud permissions.

## Overview
- **Category:** industry-titans
- **Price:** Free
- **Tags:** event-driven, message-queue, asynchronous, pub-sub, data-streaming, webhook

## Description

This MCP gives your agent one surgical ability: safely pulling and confirming messages on a designated Google Pub/Sub Subscription. Because the access scope is locked down to just this single queue, you avoid dangerous global GCP permissions entirely. Your AI client can run as a highly reliable background worker, chewing through queued tasks without ever touching other workloads or subscriptions. It uses standard polling methods for maximum reliability. If your workflow needs an autonomous way to process messages coming into Google Cloud Pub/Sub, Vinkius hosts this MCP, letting you connect it easily from any compatible AI client like Cursor or Claude.

## Tools

### acknowledge_messages
Use this to confirm message completion, which removes them permanently from the Pub/Sub Subscription queue.

### pull_messages
This tool pulls batches of messages from the configured Google Cloud Pub/Sub Subscription for processing.

## Prompt Examples

**Prompt:** 
```
Pull the latest 5 messages from the subscription.
```

**Response:** 
```
I retrieved 2 messages. The first message contains a JSON payload instructing a database backup. Here are their ackIds for when we finish processing.
```

**Prompt:** 
```
Process the first message payload and write a summary.
```

**Response:** 
```
The message data contains an alert about high CPU usage. I have created the summary report as requested.
```

**Prompt:** 
```
Acknowledge the messages using these IDs: ["ack123", "ack456"].
```

**Response:** 
```
Successfully acknowledged 2 messages. They will no longer appear in the queue.
```

## Capabilities

### Pulling queued tasks
Your agent retrieves batches of waiting messages from the configured subscription.

### Confirming message completion
The system removes processed messages from the queue, preventing them from being redelivered later.

## Use Cases

### Handling User Signups
A marketing team needs to process every new user signup event pushed into Pub/Sub. They ask their agent to first use `pull_messages` to gather the latest events, summarize them, and then use `acknowledge_messages` to confirm that all records were successfully updated in the CRM.

### Real-time Sensor Data Ingestion
An industrial IoT system publishes sensor readings to a queue. The data team connects this MCP so their agent can autonomously run, pulling batches of data using `pull_messages`, running validation checks, and confirming receipt via `acknowledge_messages`.

### Order Fulfillment Processing
A e-commerce backend pushes order fulfillment tasks to a queue. The operations team connects the MCP so their agent can pull the necessary messages with `pull_messages`, update inventory records, and then call `acknowledge_messages` once the entire transaction is complete.

### Daily Batch Job Execution
Instead of running a cron job that needs high permissions, developers use this MCP. The agent pulls messages using `pull_messages`, runs the necessary financial calculations, and then uses `acknowledge_messages` to mark the batch as complete.

## Benefits

- You gain absolute containment. The agent only interacts with this one subscription, preventing it from accessing other critical workloads or queues.
- Processing becomes reliable. By using `pull_messages` and then calling `acknowledge_messages`, you guarantee that processed tasks are removed, eliminating redelivery risks.
- It handles scale naturally. This MCP allows your AI agent to chew through millions of queued tasks without performance degradation or manual scaling concerns.
- You avoid permission overreach. Instead of granting broad global GCP permissions, this MCP limits access surgically to one subscription only.
- The workflow is clean. Your agent pulls the messages with `pull_messages`, processes them completely, and then uses `acknowledge_messages` in a predictable two-step cycle.

## How It Works

The bottom line is that you get a safe, focused mechanism to reliably process and clear out incoming message queues.

1. Your AI client uses the `pull_messages` tool to check and retrieve waiting tasks from the designated Pub/Sub Subscription.
2. After your agent processes the data within the retrieved messages, it calls `acknowledge_messages` using the provided IDs.
3. The system confirms completion, permanently removing those messages so they don't reappear in the queue.

## Frequently Asked Questions

**How does Google Pub/Sub Subscription MCP work?**
This MCP lets your AI agent act as a specialized worker for one queue. It pulls messages from that single subscription and uses the `acknowledge_messages` tool to confirm processing when finished.

**Can I use this MCP if I need to read multiple queues?**
No, this MCP is strictly scoped to a single Pub/Sub Subscription. If you have more than one queue, you'll need to connect and deploy the MCP separately for each one.

**What happens if I forget to acknowledge messages using Google Pub/Sub Subscription MCP?**
The message will not be permanently removed. The system treats it as unprocessed and will redeliver it later, which can lead to duplicate processing errors.

**Which tool do I use first with Google Pub/Sub Subscription MCP?**
You must start by calling the `pull_messages` tool. This retrieves the current batch of tasks; you cannot acknowledge anything until you have data to process.

**Is this safe for production use?**
Yes, its primary feature is safety. Because it strips away global permissions and locks access to one subscription only, it's designed specifically for secure, contained background workers.