How does this MCP reduce token counts?

It uses the compress_openapi_spec capability to remove paths you don't need and strips out any components that aren't actually used by your target endpoints.

Will the compressed spec still be valid?

Yes, the MCP uses dependency tracing to ensure that all required schemas and components remain in the file so the API remains functional.

Which AI clients can use this MCP?

You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

Can I check if an endpoint exists before compressing?

Yes, you can use the analyze_endpoint_coverage capability to verify that your target endpoints are present in the specification.

Does this work with Swagger files?

Yes, it is designed to handle both OpenAPI and Swagger specifications.

How does the compression work?

The engine uses deterministic pruning. It removes all paths not in your targetEndpoints and then traces $ref pointers to remove any schemas that are no longer reachable, ensuring the resulting spec is structurally valid.

Will my API specification break after compression?

No. The capability ensures schema integrity by performing a graph traversal. Any component or schema required by your target endpoints is strictly preserved.

Can I control the size of the output?

Yes. Using compress_openapi_spec, you can set a maxTokenBudget. The engine will iteratively truncate description fields until the specification fits within your specified budget.

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Connect OpenAPI Context Window Packer 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. Fit massive API specifications into your AI's context window.

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 OpenAPI Context Window Packer.

01
Analyze endpoint coverage
This capability checks if specific endpoints exist within your provided specification. It helps you verify that your target API surface is actually present before you start prompting.
02
Compress openapi spec
This capability prunes your OpenAPI spec by removing unnecessary paths and stripping unused components. It uses dependency tracing to keep the resulting file valid and minimal.
03
Trace schema dependencies
This capability identifies which specific schemas are required by a given endpoint. It maps out the relationship between paths and their underlying data structures.

Real work

What teams actually run

Agent Tooling

Shrink a massive enterprise API spec so an agent can use it as a toolset without hitting limits.

API Debugging

Verify that specific endpoints are correctly defined in a large Swagger file.

Token Cost Management

Minimize the number of tokens sent to your AI client by removing redundant schema definitions.

Schema Mapping

Identify exactly which data models are linked to a specific API path.

One connector, every AI

OpenAPI Context Window Packer 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 OpenAPI Context Window Packer 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

715ms average. Fast in production.

OpenAPI Context Window Packer is checked daily against the live service.

Daily averagePeak 866ms

Oct 3Today

Fastest day: 583ms
Slowest day: 866ms
14-day trend: Improving-5%

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 OpenAPI Context Window Packer, so you can see the experience inside your AI.

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

OpenAPI Context Window Packer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_XMZvUjc3wLVnJZVkg6dLaL15NgLbiiNTRgEG82fO/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 — OpenAPI Context Window Packer capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "openapi-context-window-packer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_XMZvUjc3wLVnJZVkg6dLaL15NgLbiiNTRgEG82fO/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 OpenAPI Context Window Packer in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work OpenAPI Context Window Packer owners hand off.

This MCP is built for developers building AI agents that need to interact with complex, large-scale APIs.

01
AI Engineer
They hand off massive API documentation to the MCP to create lean context for their agents.
02
Backend Developer
They use it to test if their API specs are being correctly interpreted by AI clients.
03
DevOps Engineer
They use it to manage the token costs and performance of LLM-based automation capabilities.

FAQ

Questions OpenAPI Context Window Packer owners ask.

01
How does this MCP reduce token counts?
It uses the compress_openapi_spec capability to remove paths you don't need and strips out any components that aren't actually used by your target endpoints.
02
Will the compressed spec still be valid?
Yes, the MCP uses dependency tracing to ensure that all required schemas and components remain in the file so the API remains functional.
03
Which AI clients can use this MCP?
You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.
04
Can I check if an endpoint exists before compressing?
Yes, you can use the analyze_endpoint_coverage capability to verify that your target endpoints are present in the specification.
05
Does this work with Swagger files?
Yes, it is designed to handle both OpenAPI and Swagger specifications.
06
How does the compression work?
The engine uses deterministic pruning. It removes all paths not in your targetEndpoints and then traces $ref pointers to remove any schemas that are no longer reachable, ensuring the resulting spec is structurally valid.
07
Will my API specification break after compression?
No. The capability ensures schema integrity by performing a graph traversal. Any component or schema required by your target endpoints is strictly preserved.
08
Can I control the size of the output?
Yes. Using compress_openapi_spec, you can set a maxTokenBudget. The engine will iteratively truncate description fields until the specification fits within your specified budget.

Explore

More in Developer Tools

Connect OpenAPI Context Window Packer 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 endpoint coverage

Compress openapi spec

Trace schema dependencies

What teams actually run

Agent Tooling

API Debugging

Token Cost Management

Schema Mapping

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

OpenAPI Context Window Packer Connector

Claude Desktop

AI Engineer

Backend Developer

DevOps Engineer

How does this MCP reduce token counts?

Will the compressed spec still be valid?

Which AI clients can use this MCP?

Can I check if an endpoint exists before compressing?

Does this work with Swagger files?

How does the compression work?

Will my API specification break after compression?

Can I control the size of the output?

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