Deterministic Timeout Enforcer Connector for AI agents.
3 live capabilities
Stop infinite loops and control token spending in agentic workflows
Waiting for input…
Why people use Deterministic Timeout Enforcer
Preventing runaway agent loops with Deterministic Timeout Enforcer
With this MCP, that chaos stops. You set the boundaries, and the system enforces them. It turns a wild, unpredictable agent into a disciplined worker that knows exactly when to stop and how much it's allowed to say.
What Vinkius changes
You get a kill-switch and a budget-manager for your autonomous agents.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Stopping an agent stuck in a loop
An agent is trying to solve a math problem but keeps repeating the same wrong step.
- Real-world use case 02
Managing budget for long-running research tasks
A researcher agent is digging through documents.
- Real-world use case 03
Scaling multi-agent swarms
When running dozens of agents at once, evaluate_task_safety keeps the whole swarm from hanging due to one rogue process.
Complete set · 3capabilities
The complete Deterministic Timeout Enforcer capability set.
These are the exact actions your AI can choose when you ask it to work with Deterministic Timeout Enforcer.
01—03
3 capabilities in this set.
Part of 3 available through Deterministic Timeout Enforcer.
- 01 Capability
Calculate token budget
Suggests a maximum token limit for the next LLM call. This prevents the model from attempting a response it cannot finish in time.
- 02 Capability
Check execution status
Determines if the current task has entered a danger zone. It tells you if the task must stop to respect your safety margin.
- 03 Capability
Evaluate task safety
Checks if a task should terminate and provides the token budget for the next step. It's a single capability for both safety and budgeting.
Set up in minutes
One URL. Then ask Deterministic Timeout Enforcer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Deterministic Timeout Enforcer 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_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Deterministic Timeout Enforcer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer URL.
- Step 03
Save and start
Save the connection and enable Deterministic Timeout Enforcer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-timeout-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer
Open Agent mode in chat and ask: "Using Deterministic Timeout Enforcer, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-timeout-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer
Ask Copilot: "Using Deterministic Timeout Enforcer, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-timeout-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer
Open Cascade and ask: "Using Deterministic Timeout Enforcer, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"deterministic-timeout-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer
Ask Cline: "Using Deterministic Timeout Enforcer, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add deterministic-timeout-enforcer --transport http "https://edge.vinkius.com/vk_preview_TjR6dvLKjHOYH4GEv5Sys65NLcQkEQQfQfbIfK1a/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 Deterministic Timeout Enforcer
Ask Claude: "Using Deterministic Timeout Enforcer, show me...". 3 tools are ready
Where the request belongs
Work Deterministic Timeout Enforcer can move forward.
This is for developers and AI engineers building complex, multi-agent systems that need to run reliably without manual supervision.
AI Engineer
Building autonomous loops in frameworks like AutoGen or CrewAI and needing to prevent runaway costs.
LLM Ops Engineer
Managing production-grade agent deployments where predictable execution time is a requirement.
Agentic Workflow Developer
Designing multi-step reasoning chains that might otherwise get stuck in repetitive loops.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
Circuit Breaker State Manager
Prevents cascading failures by managing service health states.
Retry with Backoff Executor
Deterministic retry logic with exponential backoff and jitter for LLM API calls.
Global Retry Budget Tracker
Prevents unbounded retry loops by enforcing a strict credit-based budget across all agents.
Execution Circuit Breaker
Prevent cascading failures by monitoring consecutive errors and managing execution permissions.
X Ads (Twitter)
Connect your X Ads account to any AI agent. audit campaigns, analyze line item performance, and pull engagement reports through natural conversation.
Box
Store, share, and collaborate on files securely with enterprise-grade cloud content management and governance controls.
Bring your own AI
Change the model, client or framework. Keep Deterministic Timeout Enforcer connected.
-
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 Deterministic Timeout Enforcer.
The practical details behind the request, access and result.
How does Deterministic Timeout Enforcer prevent infinite loops?
It monitors the elapsed time of a task against a safety margin. If the agent takes too long, the MCP triggers a stop command to prevent the loop from continuing indefinitely.
Can I use Deterministic Timeout Enforcer with any agent framework?
Yes, as long as your framework can call an MCP capability during its execution loop, it works with AutoGen, CrewAI, and custom-built agentic systems.
Will this MCP help me save money on LLM API calls?
Yes. By using the token budgeting features, you prevent agents from generating massive, unnecessary responses that consume your credits.
How does the token budget calculation work?
It looks at how much time you have left in the task and compares it to the current speed (throughput) of the model to suggest a realistic limit.
Is this MCP better than just setting a max_tokens parameter?
Yes, because max_tokens is static. This MCP is dynamic; it adjusts based on how much time is actually left in your specific task execution.
How does this prevent agent hang-ups?
It uses check_execution_status to monitor the time remaining until the global deadline. If the time left is less than or equal to the safety margin, it signals for immediate termination.
What is the purpose of the token budget?
The calculate_token_budget capability predicts how many tokens an LLM can generate within the remaining time, preventing the model from starting a response it cannot complete.
Can I use a single capability for both checks?
Yes, evaluate_task_safety is a unified capability that checks the safety margin and provides the suggested token budget in one call.
One connection away
Give your agent a direct line to Deterministic Timeout Enforcer.
Connect Deterministic Timeout Enforcer once. Keep it beside 6,100+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available