Sliding Window Rate Limiter Connector for AI agents.
3 live capabilities
Prevent API 429 errors with precise request quota management.
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Why people use Sliding Window Rate Limiter
Stop API 429 errors with Sliding Window Rate Limiter
With this Connector, that guesswork disappears. Your agent knows the state of your quota before it even attempts a call, ensuring every request is authorized and safe.
What Vinkius changes
You stop hitting 4/29 errors by knowing exactly when to send your next request.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Preventing agent collisions
When multiple agents try to hit a single LLM endpoint simultaneously, use this Connector to queue them properly.
- Real-world use case 02
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.
- Real-world use case 03
Monitoring quota depletion
A developer checks usage percentages via `summarize_usage` to decide when to scale up their API tier.
Complete set · 3capabilities
The complete Sliding Window Rate Limiter capability set.
These are the exact actions your AI can choose when you ask it to work with Sliding Window Rate Limiter.
01—03
3 capabilities in this set.
Part of 3 available through Sliding Window Rate Limiter.
- 01 Capability
Check rate limit
Determines if a specific request can proceed under the current rate limit configuration
- 02 Capability
Get provider quotas
Retrieves the currently configured rate limit definitions for a specific provider
- 03 Capability
Get usage summary
Provides an overview of current consumption across all models for a given provider
Set up in minutes
One URL. Then ask Sliding Window Rate Limiter to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Sliding Window Rate Limiter from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it Sliding Window Rate Limiter, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Sliding Window Rate Limiter for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the Sliding Window Rate Limiter URL.
- Step 03
Save and start
Save the connection and enable Sliding Window Rate Limiter in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"sliding-window-rate-limiter": {
"url": "https://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp"
}
}
} - Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using Sliding Window Rate Limiter
Open Agent mode in chat and ask: "Using Sliding Window Rate Limiter, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"sliding-window-rate-limiter": {
"url": "https://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp"
}
}
} - Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using Sliding Window Rate Limiter
Ask Copilot: "Using Sliding Window Rate Limiter, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"sliding-window-rate-limiter": {
"url": "https://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp"
}
}
} - Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using Sliding Window Rate Limiter
Open Cascade and ask: "Using Sliding Window Rate Limiter, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"sliding-window-rate-limiter": {
"url": "https://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp"
}
}
} - Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using Sliding Window Rate Limiter
Ask Cline: "Using Sliding Window Rate Limiter, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add sliding-window-rate-limiter --transport http "https://edge.vinkius.com/vk_preview_USHbDW02FrEsJzJcyKPDZVpinU9suBOgDwu60VwU/mcp" - Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using Sliding Window Rate Limiter
Ask Claude: "Using Sliding Window Rate Limiter, show me...". 3 tools are ready
Where the request belongs
Work Sliding Window Rate Limiter can move forward.
Backend engineers and AI orchestrators who are tired of debugging broken pipelines caused by unexpected rate limits.
DevOps Engineer
Managing API stability across large-scale agent deployments.
AI Agent Developer
Ensuring multi-agent workflows don't overwhelm downstream services.
Backend Architect
Designing resilient systems that handle bursty traffic without manual intervention.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsAPI Rate Limit Calculator
Predict API exhaustion and simulate traffic-shaping algorithms.
Unkey API Management
Manage and verify your user API keys via Unkey. create, revoke, and track usage directly from any AI agent.
WebSocket Capacity Planner
Estimate WebSocket connection limits, server fleet requirements, and network overhead.
Message Queue Throughput Calculator
Plan capacity for Kafka, RabbitMQ, or SQS by calculating consumer needs, backlog drain time, and concurrency.
Treblle
Monitor, document, and analyze your API traffic in real-time. Ingest request and response data directly into Treblle for instant observability.
Moesif
Monitor and analyze API traffic with Moesif. log events, track user/company profiles, and query API analytics directly from your AI agent.
Bring your own AI
Change the model, client or framework. Keep Sliding Window Rate Limiter connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about Sliding Window Rate Limiter.
The practical details behind the request, access and result.
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 Connector 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 Connector?
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.
How does the sliding window approach differ from a fixed window?
Unlike fixed windows that reset at specific intervals, the sliding window tracks individual request timestamps. This prevents 'bursting' where double the allowed limit is processed right at the boundary of two windows.
Can I use this to manage OpenAI API limits?
Yes. By using evaluate_request with your provider's specific window and request limit, you can ensure your agents never trigger a 429 Too Many Requests error.
What does `get_window_density` tell me?
It provides a percentage of how much of your current window capacity is currently occupied by active requests, helping you monitor usage intensity.
How does this prevent 429 errors?
It uses check_rate_limit to determine if a request will exceed the quota. If the limit is reached, it provides the exact sleep_time_ms to wait, ensuring agents stay within the allowed window.
What is the difference between fixed and sliding windows?
Fixed windows reset at static time blocks, while sliding windows use a moving period relative to the current timestamp for smoother enforcement.
Can I monitor my current usage?
Yes, you can use get_usage_summary to see the usage percentage and status for each model under a specific provider.
One connection away
Give your agent a direct line to Sliding Window Rate Limiter.
Connect Sliding Window Rate Limiter once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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