What methods does this MCP use for prediction?

It uses the Chou-Fasman statistical propensity method and the GOR information theory approach.

Can I compare two different prediction models?

Yes, you can use the compare_prediction_methods capability to see the differences between Chou-Fasman and GOR for a single sequence.

Does the GOR method have any requirements?

Yes, the GOR method requires a minimum sequence length to perform window calculations.

What kind of structural data can I get?

You can get the distribution of alpha-helices, beta-sheets, and coils for a given sequence.

How do I use this with Claude or Cursor?

You connect your client to Vinkius once, and the capabilities become available as functions your agent can call.

What methods are used for prediction?

The server implements the Chou-Fasman statistical propensity method and the GOR (Garnier-Osguthorpe-Robson) information theory approach.

How can I compare different prediction results?

You can use the compare_prediction_methods capability to run both Chou-Fasman and GOR algorithms on the same sequence and see the differences in helix and sheet percentages.

What input format is required?

The capabilities require a string representing the primary amino acid sequence using standard single-letter codes (e.g., 'MVLSA').

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Connect Protein Secondary Structure Predictor 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. Turn amino acid sequences into structural predictions instantly.

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 · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Protein Structure Predictor.

01
Get amino acid propensities
This capability provides the specific propensity values for amino acids required for secondary structure modeling.
02
Predict structure chou fasman
This capability calculates protein secondary structure using the Chou-Fasman statistical propensity method.
03
Predict structure gor
This capability uses the GOR information theory approach to predict structure, provided the sequence meets the minimum length requirements.
04
Compare prediction methods
This capability runs both Chou-Fasman and GOR models on a single sequence to highlight differences in their results.

Real work

What teams actually run

Sequence Analysis

You provide a primary amino acid sequence to get a breakdown of alpha-helices and beta-sheets.

Model Validation

You use the comparison capability to see if Chou-Fasman or GOR provides a more consistent result for a specific sequence.

Data Preparation

You retrieve amino acid propensity values to inform other structural modeling tasks.

Structural Bias Detection

You identify how different mathematical approaches influence the predicted coil or sheet percentages.

One connector, every AI

Protein Structure Predictor 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 Protein Structure Predictor 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

881ms average. Fast in production.

Protein Structure Predictor is checked daily against the live service.

Daily averagePeak 1087ms

Oct 5Today

Fastest day: 712ms
Slowest day: 1087ms
14-day trend: Slowing+16%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 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 Protein Structure Predictor, so you can see the experience inside your AI.

It does not authenticate your account with Protein Structure Predictor. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Protein Structure Predictor Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_ikmfZm8xYgozQnq0BgBnevedFolkZQC9ZWtLxBQb/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 — Protein Structure Predictor capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "protein-secondary-structure-predictor-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ikmfZm8xYgozQnq0BgBnevedFolkZQC9ZWtLxBQb/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 Protein Structure Predictor in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Protein Structure Predictor owners hand off.

This MCP is built for researchers working in computational biology and structural proteomics.

01
Bioinformaticians
They hand off raw sequences to the agent to quickly get structural distributions.
02
Structural Biologists
They use the capability to validate sequence-based predictions against known models.
03
Computational Chemists
They use the comparison capabilities to evaluate different prediction methodologies.

FAQ

Questions Protein Structure Predictor owners ask.

01
What methods does this MCP use for prediction?
It uses the Chou-Fasman statistical propensity method and the GOR information theory approach.
02
Can I compare two different prediction models?
Yes, you can use the compare_prediction_methods capability to see the differences between Chou-Fasman and GOR for a single sequence.
03
Does the GOR method have any requirements?
Yes, the GOR method requires a minimum sequence length to perform window calculations.
04
What kind of structural data can I get?
You can get the distribution of alpha-helices, beta-sheets, and coils for a given sequence.
05
How do I use this with Claude or Cursor?
You connect your client to Vinkius once, and the capabilities become available as functions your agent can call.
06
What methods are used for prediction?
The server implements the Chou-Fasman statistical propensity method and the GOR (Garnier-Osguthorpe-Robson) information theory approach.
07
How can I compare different prediction results?
You can use the compare_prediction_methods capability to run both Chou-Fasman and GOR algorithms on the same sequence and see the differences in helix and sheet percentages.
08
What input format is required?
The capabilities require a string representing the primary amino acid sequence using standard single-letter codes (e.g., 'MVLSA').

Explore

More in Science

Connect Protein Structure Predictor 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.

01-04

Get amino acid propensities

Predict structure chou fasman

Predict structure gor

Compare prediction methods

What teams actually run

Sequence Analysis

Model Validation

Data Preparation

Structural Bias Detection

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

Protein Structure Predictor Connector

Claude Desktop

Bioinformaticians

Structural Biologists

Computational Chemists

What methods does this MCP use for prediction?

Can I compare two different prediction models?

Does the GOR method have any requirements?

What kind of structural data can I get?

How do I use this with Claude or Cursor?

What methods are used for prediction?

How can I compare different prediction results?

What input format is required?

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