Will this delete my system instructions?

No. The MCP treats system instructions and the first user message as immutable, so they are never pruned.

How does it decide which messages to remove?

It uses relevance scores for middle-tier messages, keeping the most important content that fits your token budget.

Can I use this with Cursor or Windsurf?

Yes. This MCP works with any MCP-compatible client, including Cursor, Windsurf, and VS Code.

Does it keep my recent messages?

Yes. It maintains a protected buffer of recent messages to ensure the immediate context remains intact.

How do I know how many tokens I'll save?

You can use the predict_pruning_impact capability to simulate a strategy and see the expected token reduction before executing it.

What makes the pruning process deterministic?

The process follows strict, unchangeable rules: it always preserves system messages and the first user message, protects a recent buffer of N messages, and then selects middle messages based on their relevance score until the token budget is reached.

How can I see how much space my current conversation is using?

You can use the analyze_context_density capability. It will break down your message list into immutable, buffer, and prunable token counts.

Can I simulate a pruning run before actually deleting messages?

Yes, the predict_pruning_impact capability allows you to estimate how many tokens will be saved and what information will remain without modifying your actual message list.

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Connect Memory Context Priority Pruner to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Keep your AI focused by managing its memory limits.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Memory Context Priority Pruner.

01
Analyze context density
This capability audits your current token usage by checking how they are distributed across different message tiers.
02
Execute context reduction
This capability performs the actual removal of messages to bring your conversation back under your target token limit.
03
Predict pruning impact
Use this to simulate how a specific pruning strategy will change your token count before you actually apply it.

Real work

What teams actually run

Long-Running Coding Sessions

Keep your agent focused on the current file and task even after hours of debugging and chat history buildup.

Agentic Workflows

Ensure autonomous agents don't exceed token limits during multi-step reasoning tasks.

Cost Management

Reduce token consumption by stripping out unnecessary middle-tier conversation history.

Instruction Integrity

Prevent the agent from 'forgetting' its core persona or rules during extended interactions.

One connector, every AI

Memory Context Priority Pruner works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

Building your own app? The connector is yours to use.

You don't need a client to put Memory Context Priority Pruner to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

701ms average. Fast in production.

Memory Context Priority Pruner is checked daily against the live service.

Daily averagePeak 831ms

Oct 3Today

Fastest day: 557ms
Slowest day: 831ms
14-day trend: Improving-15%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Memory Context Priority Pruner, so you can see the experience inside your AI.

It does not authenticate your account with Memory Context Priority Pruner. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Memory Context Priority Pruner Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_wn6QQ6MBDELDQuy390LTPIrEYUANWateQNUsl4sW/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — Memory Context Priority Pruner capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "memory-context-priority-pruner-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_wn6QQ6MBDELDQuy390LTPIrEYUANWateQNUsl4sW/mcp"
    }
  }
}

Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Memory Context Priority Pruner in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Memory Context Priority Pruner owners hand off.

This is for anyone building or using long-running AI agents that need to stay within technical limits.

01
AI Engineers
They hand off complex conversation histories to agents that need to remain performant.
02
Prompt Engineers
They use it to ensure system instructions aren't lost during long sessions.
03
Workflow Automators
They manage token costs and window limits for automated agentic tasks.

FAQ

Questions Memory Context Priority Pruner owners ask.

01
Will this delete my system instructions?
No. The MCP treats system instructions and the first user message as immutable, so they are never pruned.
02
How does it decide which messages to remove?
It uses relevance scores for middle-tier messages, keeping the most important content that fits your token budget.
03
Can I use this with Cursor or Windsurf?
Yes. This MCP works with any MCP-compatible client, including Cursor, Windsurf, and VS Code.
04
Does it keep my recent messages?
Yes. It maintains a protected buffer of recent messages to ensure the immediate context remains intact.
05
How do I know how many tokens I'll save?
You can use the predict_pruning_impact capability to simulate a strategy and see the expected token reduction before executing it.
06
What makes the pruning process deterministic?
The process follows strict, unchangeable rules: it always preserves system messages and the first user message, protects a recent buffer of N messages, and then selects middle messages based on their relevance score until the token budget is reached.
07
How can I see how much space my current conversation is using?
You can use the analyze_context_density capability. It will break down your message list into immutable, buffer, and prunable token counts.
08
Can I simulate a pruning run before actually deleting messages?
Yes, the predict_pruning_impact capability allows you to estimate how many tokens will be saved and what information will remain without modifying your actual message list.

Explore

More in AI Infrastructure

Connect Memory Context Priority Pruner to Claude, Cursor, ChatGPT & more

Your AI does the work. We keep it safe and sound.

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-03

Analyze context density

Execute context reduction

Predict pruning impact

What teams actually run

Long-Running Coding Sessions

Agentic Workflows

Cost Management

Instruction Integrity

Building your own app? The connector is yours to use.

Memory Context Priority Pruner Connector

Claude Desktop

AI Engineers

Prompt Engineers

Workflow Automators

Will this delete my system instructions?

How does it decide which messages to remove?

Can I use this with Cursor or Windsurf?

Does it keep my recent messages?

How do I know how many tokens I'll save?

What makes the pruning process deterministic?

How can I see how much space my current conversation is using?

Can I simulate a pruning run before actually deleting messages?

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