Agent Memory Tier Calculator Connector for AI agents.
3 live capabilities
Optimize agentic memory hierarchies and retrieval latency
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Why people use Agent Memory Tier Calculator
Solve agentic memory bottlenecks with Agent Memory Tier Calculator
With this MCP, you stop guessing. You can actually model the movement of data through your hierarchy. You'll know exactly when a piece of information is being pushed out of working memory and how that impacts your retrieval speed. It turns memory management from a guessing game into a precise engineering task.
What Vinkius changes
You get a mathematical blueprint for your agent's memory instead of relying on trial and error.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,400+ Connectors
- Real-world use case 01
Fixing an agent that keeps forgetting context
An engineer notices their agent loses the thread during long conversations.
- Real-world use case 02
Reducing latency in production agents
A developer sees high response times.
- Real-world use case 03
Right-sizing memory for a new deployment
Before launching a new agent, a researcher uses optimize_working_memory to determine the minimum token count needed to maintain a 90% hit rate.
Complete set · 3capabilities
The complete Agent Memory Tier Calculator capability set.
These are the exact actions your AI can choose when you ask it to work with Agent Memory Tier Calculator.
01—03
3 capabilities in this set.
Part of 3 available through Agent Memory Tier Calculator.
- 01 Capability
Calculate memory lifecycle
Calculates the movement and current state of all memory tiers. Use this to see how data is being promoted or evicted.
- 02 Capability
Optimize working memory
Determines the ideal size for working memory. This helps you hit specific hit rate targets without wasting resources.
- 03 Capability
Simulate retrieval performance
Tests the efficiency of your memory setup. It provides data on latency and hit rates for your specific access patterns.
Set up in minutes
One URL. Then ask Agent Memory Tier Calculator to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Agent Memory Tier Calculator 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_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Agent Memory Tier Calculator for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator URL.
- Step 03
Save and start
Save the connection and enable Agent Memory Tier Calculator in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-memory-tier-calculator": {
"url": "https://edge.vinkius.com/vk_preview_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator
Open Agent mode in chat and ask: "Using Agent Memory Tier Calculator, help me...". 3 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-memory-tier-calculator": {
"url": "https://edge.vinkius.com/vk_preview_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator
Ask Copilot: "Using Agent Memory Tier Calculator, help me...". 3 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-memory-tier-calculator": {
"url": "https://edge.vinkius.com/vk_preview_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator
Open Cascade and ask: "Using Agent Memory Tier Calculator, help me...". 3 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"agent-memory-tier-calculator": {
"url": "https://edge.vinkius.com/vk_preview_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator
Ask Cline: "Using Agent Memory Tier Calculator, help me...". 3 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add agent-memory-tier-calculator --transport http "https://edge.vinkius.com/vk_preview_VjXg1lmsFMEFMjb9yRqgsOO6gwn4M5LRWbqCt3Ir/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 Agent Memory Tier Calculator
Ask Claude: "Using Agent Memory Tier Calculator, show me...". 3 tools are ready
Where the request belongs
Work Agent Memory Tier Calculator can move forward.
This is for the engineers and researchers building autonomous agents who are tired of agents 'forgetting' things or becoming too slow to be useful.
AI Engineer
Tuning the memory architecture of a new agentic system to balance cost and performance.
MLOps Engineer
Monitoring and optimizing the retrieval latency of deployed agentic workflows.
Agentic Researcher
Simulating how different memory hierarchies affect agent intelligence and reasoning.
Build the capability set
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Bring your own AI
Change the model, client or framework. Keep Agent Memory Tier Calculator connected.
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Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
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LibreChat -
TypingMind -
Chorus -
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CrewAI -
Vercel AI SDK
Before you connect
Questions about Agent Memory Tier Calculator.
The practical details behind the request, access and result.
How can the Agent Memory Tier Calculator help my AI agents?
It provides the mathematical capabilities to manage how your agents store and retrieve information. You can calculate how data moves between memory tiers to ensure your agent stays fast and doesn't forget important details.
Can I use Agent Memory Tier Calculator to reduce agent latency?
Yes. By using the simulation capabilities, you can identify which memory configurations result in the fastest retrieval times and adjust your working memory size to minimize delays.
How does Agent Memory Tier Calculator handle memory eviction?
It calculates the specific flows of how data is demoted from active memory to long-term storage, helping you prevent the agent from losing critical context too early.
Is the Agent Memory Tier Calculator useful for cost optimization?
Absolutely. It helps you find the smallest possible working memory size needed to maintain your required hit rate, preventing you from overspending on unnecessary context windows.
Does Agent Memory Tier Calculator work with any agentic framework?
Yes, as long as your framework is compatible with the Model Context Protocol, you can use this MCP to manage its memory hierarchies.
How does the system decide which memory to demote?
The system uses a scoring metric combining recency, frequency, and importance. When a tier reaches capacity, the memory with the lowest score is demoted to the next tier or evicted.
What is thrashing in the context of memory management?
Thrashing occurs when Working Memory utilization exceeds 95%, causing rapid, repetitive demotions and promotions that degrade agent performance.
Can I optimize my agent's performance?
Yes, you can use optimize_working_memory to calculate the minimum token capacity required to achieve a specific cache hit rate target.
One connection away
Give your agent a direct line to Agent Memory Tier Calculator.
Connect Agent Memory Tier Calculator once. Keep it beside 6,400+ managed Connectors when the next task needs more.
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