How does this MCP save tokens?

It uses three specific strategies: sliding windows to drop old turns, summary injection to condense old turns, and importance-based logic to keep only key information.

Will my AI forget everything if I compress the conversation?

Not if you use summary injection. That strategy turns old messages into a condensed summary so the semantic meaning stays in the context window.

Can I check if the compression worked well?

Yes, you can use the evaluation capability to check the continuity score and ensure the reduction wasn't too aggressive.

Which AI clients can use this MCP?

Any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code can use this capability once connected through Vinkius.

What is the difference between sliding window and summary injection?

Sliding window simply deletes the oldest messages, while summary injection rewrites them into a shorter version to preserve meaning.

How does the sliding window strategy work?

The sliding_window strategy uses a FIFO method to keep only the most recent turns within the specified token limit, ensuring the model has immediate context.

Can I ensure my system prompt is never lost?

Yes. The engine includes strict preservation rules that ensure the system prompt is always kept as the first element and is immune to all compression logic.

How do I know if the compression was too aggressive?

You can use the evaluate_compression_quality_tool to check metrics. It flags results if token savings are below 20% or if the continuity score falls below 0.3.

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Connect Multi-Turn Conversation Compressor to your AI

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 agents within context limits without losing the thread.

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 · 2 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-02

2 capabilities in this set.

Part of 2 available through Multi-Turn Conversation Compressor.

01
Compress conversation tool
This capability executes the mathematical strategies to shrink your conversation history. It applies sliding windows, summaries, or importance-based logic to reduce token counts.
02
Evaluate compression quality tool
This capability analyzes the results of a compression task. It checks if the reduction was too aggressive or if the conversational continuity remains high enough for the agent to function.

Real work

What teams actually run

Long-running Chatbots

Use summary injection to keep a customer support bot aware of the entire interaction without hitting limits.

Autonomous Agent Loops

Apply a sliding window to keep an agent focused on its current task while discarding old, irrelevant steps.

Cost Optimization

Use importance-based compression to strip out fluff and only pay for the tokens that actually matter.

Context Quality Auditing

Run quality evaluations to ensure your compression settings aren't making your agent lose its mind.

One connector, every AI

Multi-Turn Conversation Compressor 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 Multi-Turn Conversation Compressor 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

905ms average. Fast in production.

Multi-Turn Conversation Compressor is checked daily against the live service.

Daily averagePeak 1209ms

Oct 3Today

Fastest day: 689ms
Slowest day: 1209ms
14-day trend: Improving-21%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 2 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 Multi-Turn Conversation Compressor, so you can see the experience inside your AI.

It does not authenticate your account with Multi-Turn Conversation Compressor. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Multi-Turn Conversation Compressor Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_cjy6h1h0uYGQWAPoJ9znJlexxrxgUhzuV2rz9OFE/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 — Multi-Turn Conversation Compressor capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "multi-turn-conversation-compressor-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_cjy6h1h0uYGQWAPoJ9znJlexxrxgUhzuV2rz9OFE/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 Multi-Turn Conversation Compressor in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Multi-Turn Conversation Compressor owners hand off.

This MCP is built for developers and researchers working with long-running AI agents that struggle with context window constraints.

01
AI Engineers
They hand off long conversation logs to the MCP to optimize agent performance and reduce costs.
02
LLM Researchers
They use the compression quality capabilities to study how different reduction strategies affect model reasoning.
03
Agentic Workflow Developers
They integrate this into autonomous loops to prevent agents from crashing due to context overflow.

FAQ

Questions Multi-Turn Conversation Compressor owners ask.

01
How does this MCP save tokens?
It uses three specific strategies: sliding windows to drop old turns, summary injection to condense old turns, and importance-based logic to keep only key information.
02
Will my AI forget everything if I compress the conversation?
Not if you use summary injection. That strategy turns old messages into a condensed summary so the semantic meaning stays in the context window.
03
Can I check if the compression worked well?
Yes, you can use the evaluation capability to check the continuity score and ensure the reduction wasn't too aggressive.
04
Which AI clients can use this MCP?
Any MCP-compatible client like Claude, Cursor, Windsurf, or VS Code can use this capability once connected through Vinkius.
05
What is the difference between sliding window and summary injection?
Sliding window simply deletes the oldest messages, while summary injection rewrites them into a shorter version to preserve meaning.
06
How does the sliding window strategy work?
The sliding_window strategy uses a FIFO method to keep only the most recent turns within the specified token limit, ensuring the model has immediate context.
07
Can I ensure my system prompt is never lost?
Yes. The engine includes strict preservation rules that ensure the system prompt is always kept as the first element and is immune to all compression logic.
08
How do I know if the compression was too aggressive?
You can use the evaluate_compression_quality_tool to check metrics. It flags results if token savings are below 20% or if the continuity score falls below 0.3.

Explore

More in Context Management

Connect Multi-Turn Conversation Compressor 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.

01-02

Compress conversation tool

Evaluate compression quality tool

What teams actually run

Long-running Chatbots

Autonomous Agent Loops

Cost Optimization

Context Quality Auditing

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

Multi-Turn Conversation Compressor Connector

Claude Desktop

AI Engineers

LLM Researchers

Agentic Workflow Developers

How does this MCP save tokens?

Will my AI forget everything if I compress the conversation?

Can I check if the compression worked well?

Which AI clients can use this MCP?

What is the difference between sliding window and summary injection?

How does the sliding window strategy work?

Can I ensure my system prompt is never lost?

How do I know if the compression was too aggressive?

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