# Sliding Window Rate Limiter MCP for AI Agents MCP

> Sliding Window Rate Limiter MCP manages API request quotas using a continuous window. It prevents overload in multi-agent systems by tracking active requests and calculating exact wait times before capacity opens up.

## Overview
- **Category:** infrastructure
- **Price:** Free
- **Endpoint:** https://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp
- **Tags:** api, rate-limit, sliding-window, quota-management, multi-agent

## Description

Running multiple agents that all hit the same API endpoint is a recipe for disaster. Without control, they crash into each other, trigger 429 errors, and break your entire pipeline. This MCP acts as a traffic controller for your agentic workflows. Instead of using rigid windows that reset at arbitrary times and cause massive spikes, it uses a continuous window to track every request in a moving timeframe. You don't have to guess if a call will fail; you can see the exact millisecond when it becomes safe to try again. When you connect this via Vinkius, you get an instant way to keep your automation from hitting walls. It keeps your history clean and your usage visible so you aren't flying blind during high-traffic periods.

## Tools

### prune_history
Deletes old timestamps to keep your tracking window efficient and fast. This prevents unnecessary memory bloat.

### summarize_usage
Shows you a high-level view of how much capacity is currently being used. It provides an instant percentage of usage.

### validate_request
Checks if an incoming call is permitted and tells you how long to wait. This prevents failed API calls before they happen.

## Prompt Examples

**Prompt:** 
```
Can I make another request to my database right now?
```

**Response:** 
```
Checking current window status...

| Metric | Value |
| :--- | :--- |
| **Status** | **Denied** |
| Current Count | 10 |
| Limit | 10 |
| **Wait Time** | **4,200ms** |

You must wait approximately 4 seconds before the next request is permitted.
```

**Prompt:** 
```
How much of my API quota is left?
```

**Response:** 
```
You have used **15%** of your allocated capacity. You currently have **85** requests remaining in your active window.
```

**Prompt:** 
```
Clean up my request history for the last minute.
```

**Response:** 
```
I have processed the history cleanup. All timestamps older than 60 seconds were removed to maintain system efficiency.
```

## Capabilities

### Check request permission
Determine if a new call is allowed or if it needs to wait for capacity.

### Monitor capacity
See exactly what percentage of your quota is currently being used.

### Automate cleanup
Remove old, irrelevant data to keep the tracking window efficient.

### Calculate wait times
Get precise millisecond values for when a new slot opens up.

### Track active requests
Maintain an accurate count of all calls within your moving timeframe.

## Use Cases

### Preventing agent collisions
When multiple agents try to hit a single LLM endpoint simultaneously, use this MCP to queue them properly.

### Managing bursty API traffic
An engineer uses `validate_request` to ensure a sudden spike in tasks doesn't trigger a lockout from a critical service.

### Monitoring quota depletion
A developer checks usage percentages via `summarize_usage` to decide when to scale up their API tier.

## Benefits

- Stop hitting rate limits by knowing exactly when a new slot is available.
- Reduce error handling logic in your agents using `validate_request`.
- Keep your system lightweight by automatically running `prune_history`.
- Get instant visibility into your API consumption with `summarize_usage`.
- Avoid the fixed window trap where limits reset at arbitrary times and cause spikes.

## How It Works

The bottom line is you stop hitting 4/29 errors by knowing exactly when to send your next request.

1. Connect your preferred client to the MCP via Vinkius.
2. Configure your specific request limits and window duration.
3. Your agent checks the current state before executing any external API calls.

## Frequently Asked Questions

**How does Sliding Window Rate Limiter prevent API errors?**
It tracks every request in a moving timeframe, allowing your agent to see if a call will be blocked before it even happens.

**Can I use Sliding Window Rate Limiter with Claude or Cursor?**
Yes. Any MCP-compatible client like Claude, Cursor, or Windsurf can connect to this MCP to manage your API traffic.

**Does the Sliding Window Rate Limiter help with multi-agent systems?**
Absolutely. It is designed specifically to coordinate shared quotas across multiple agents so they don't overwhelm a single service.

**How do I check my current API usage with this MCP?**
You can simply ask your agent for a summary of your usage, and it will provide the current percentage of capacity used.

**Will the Sliding Window Rate Limiter slow down my requests?**
No. The check happens almost instantly, adding negligible latency to your existing workflow.

**How does the sliding window differ from a fixed window?**
A fixed window resets at specific clock intervals (e.g., every hour), which can allow bursts of traffic at the boundary. A sliding window uses a continuous timeframe, ensuring that the number of requests is always measured against the most recent duration.

**Can I use `validate_request` to prevent API key exhaustion?**
Yes. By tracking your request timestamps and using `validate_request`, you can proactively check if a new request will exceed your quota before actually making the call, saving both time and resources.

**What is the purpose of `prune_history`?**
`prune_history` removes timestamps that have moved past the sliding boundary into the expired zone, keeping your request history array small and efficient for subsequent calculations.