Token Counter and Budget Enforcer Connector for AI agents.
3 live capabilities
Control LLM token spending and enforce strict budget limits.
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Why people use Token Counter and Budget Enforcer
Stop LLM cost spikes with Token Counter and Budget Enforcer
With this MCP, that anxiety disappears. You move from reactive damage control to proactive management. You can predict costs before they happen and set hard stops that actually work, giving you total control over your AI operations.
What Vinkius changes
You get a programmable safety net that prevents AI agents from exceeding your budget.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Preventing runaway agent loops
An engineer sets a limit for a research agent.
- Real-world use case 02
Pre-flight cost estimation
A developer uses estimate_tokens to check a massive codebase before passing it to an agent, ensuring it fits within the expected context window and budget.
- Real-world use case 03
Multi-tenant cost tracking
A platform provider uses get_usage_summary to monitor how much each user's agent is consuming to ensure accurate billing.
Complete set · 3capabilities
The complete Token Counter and Budget Enforcer capability set.
These are the exact actions your AI can choose when you ask it to work with Token Counter and Budget Enforcer.
01—03
3 capabilities in this set.
Part of 3 available through Token Counter and Budget Enforcer.
- 01 Capability
Estimate tokens
Calculates the estimated token count for a provided text string. Use this to predict costs before sending large payloads.
- 02 Capability
Get usage summary
Retrieves current cumulative totals without consuming new tokens. It's perfect for checking your current spend status.
- 03 Capability
Track and enforce usage
Updates the cumulative usage for an agent and a conversation, then checks against set limits. This is your primary budget guardrail.
Set up in minutes
One URL. Then ask Token Counter and Budget Enforcer to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Token Counter and Budget 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_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Token Counter and Budget Enforcer for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer URL.
- Step 03
Save and start
Save the connection and enable Token Counter and Budget Enforcer in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"token-counter-and-budget-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer
Open Agent mode in chat and ask: "Using Token Counter and Budget Enforcer, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"token-counter-and-budget-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer
Ask Copilot: "Using Token Counter and Budget Enforcer, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"token-counter-and-budget-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer
Open Cascade and ask: "Using Token Counter and Budget Enforcer, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"token-counter-and-budget-enforcer": {
"url": "https://edge.vinkius.com/vk_preview_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer
Ask Cline: "Using Token Counter and Budget Enforcer, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add token-counter-and-budget-enforcer --transport http "https://edge.vinkius.com/vk_preview_Fntor1z8zuXrJce6K2HdextT8uXupjEA6h8NsXAn/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 Token Counter and Budget Enforcer
Ask Claude: "Using Token Counter and Budget Enforcer, show me...". 3 tools are ready
Where the request belongs
Work Token Counter and Budget Enforcer can move forward.
This is for developers and engineers who are tired of checking cloud provider dashboards to see why their LLM bill spiked overnight.
AI Engineer
Managing multi-agent orchestration where individual agent costs can spiral out of control.
DevOps Engineer
Setting up guardrails for automated workflows to ensure predictable operational expenses.
Product Manager
Monitoring the cost-to-serve for AI features to ensure they stay within profitable margins.
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Bring your own AI
Change the model, client or framework. Keep Token Counter and Budget Enforcer connected.
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Before you connect
Questions about Token Counter and Budget Enforcer.
The practical details behind the request, access and result.
How can I prevent my AI agents from spending too much money?
You can use the Token Counter and Budget Enforcer MCP to set strict limits. It tracks usage and can automatically stop an agent once it hits its budget.
Can I estimate the cost of a large file before sending it to an agent?
Yes, you can use the estimation capability to get a precise token count for any text or code before you process it, helping you avoid surprises.
How does the Token Counter and Budget Enforcer track usage?
It tracks cumulative token counts for both individual agents and specific conversation threads, allowing for granular budget control.
Is it possible to see a summary of my agent's total spend?
Yes, you can pull a summary at any time to see exactly how many tokens have been consumed without adding any new costs.
Will this work with my existing AI workflows?
Yes, as long as you are using an MCP-compatible client like Claude, Cursor, or Windsurf, you can connect this to manage your agent costs immediately.
How are tokens estimated?
Tokens are estimated using a deterministic character-to-token ratio: approximately 4 characters per token for English text and 3.5 characters per token for code blocks.
Can I set different limits for agents and conversations?
Yes. You can use track_and_enforce_usage to apply specific limits for both the unique agent identifier and the specific conversation identifier.
How do I check my current usage?
You can use the get_usage_summary capability to retrieve the cumulative token totals for a specific agent or conversation without consuming any new tokens.
One connection away
Give your agent a direct line to Token Counter and Budget Enforcer.
Connect Token Counter and Budget Enforcer once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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