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Connect Sentiment vs Fundamental Divergence 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. Find arbitrage opportunities by spotting social and utility gaps.

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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.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

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.

A futuristic MCP client docking bay
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 Sentiment vs Fundamental Divergence.

  1. 01

    Get historical performance

    This capability runs the divergence strategy against past datasets to see how it would have performed. Use it to validate your strategy before putting capital at risk.

  2. 02

    Calculate divergence signal

    This capability evaluates current market conditions to produce a specific BUY or SELL signal. It looks at the spread between social and fundamental Z-scores.

  3. 03

    Validate stop loss

    This capability checks if a position has hit the 15% risk threshold. It tells you if a trade has reached its maximum allowable loss.

Real work

What teams actually run

01

Spotting Overheated Markets

Your agent flags assets where social media hype has decoupled from actual on-chain usage.

02

Finding Undervalued Assets

You identify accumulation opportunities when on-chain fundamentals grow while social volume remains low.

03

Automated Risk Monitoring

Your AI client checks if a price drop has hit your 15% threshold to protect your capital.

04

Strategy Validation

You run the divergence logic against historical datasets to confirm the strategy's win rate.

One connector, every AI

Sentiment vs Fundamental Divergence 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.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

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

You don't need a client to put Sentiment vs Fundamental Divergence 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

836ms average. Fast in production.

Sentiment vs Fundamental Divergence is checked daily against the live service.

Daily averagePeak 1069ms
Oct 3Today
Fastest day
706ms
Slowest day
1069ms
14-day trend
Improving-16%

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 Sentiment vs Fundamental Divergence, so you can see the experience inside your AI.

It does not authenticate your account with Sentiment vs Fundamental Divergence. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Sentiment vs Fundamental Divergence Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_XHZAXw3RRChwpfYcFEp8Tn41jJJDYYd91f3OQZPl/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Sentiment vs Fundamental Divergence capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "sentiment-vs-fundamental-divergence-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_XHZAXw3RRChwpfYcFEp8Tn41jJJDYYd91f3OQZPl/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 Sentiment vs Fundamental Divergence in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Sentiment vs Fundamental Divergence owners hand off.

This MCP is built for traders who want to move away from pure sentiment trading and toward data-driven arbitrage.

  • 01

    Crypto Quantitative Traders

    They hand off the heavy lifting of Z-score calculations and signal generation to their agent.

  • 02

    Algorithmic Researchers

    They use the backtesting capability to validate new divergence hypotheses against historical data.

  • 03

    Risk Managers

    They use the stop-loss validation capability to monitor position health across multiple assets.

FAQ

Questions Sentiment vs Fundamental Divergence owners ask.

  • 01

    How does this MCP identify a bubble?

    It calculates Z-scores for social volume and fundamental metrics. A bubble is identified when social hype is high but on-chain utility is low.

  • 02

    What is the stop-loss threshold?

    The capability uses a fixed 15% threshold to validate if a position has reached its maximum allowable risk.

  • 03

    Can I backtest these signals?

    Yes, you can use the get_historical_performance capability to test the divergence strategy against historical datasets.

  • 04

    Which AI clients can use this MCP?

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

  • 05

    What kind of signals does it produce?

    The calculate_divergence_signal capability produces specific BUY or SELL signals based on the statistical gap between hype and utility.

  • 06

    How are the trading signals generated?

    Signals are generated using calculate_divergence_signal, which compares the Z-score of social volume against the Z-score of fundamental metrics to find extreme divergences.

  • 07

    What is the risk management strategy?

    The strategy uses a strict 15% stop-loss. You can use validate_stop_loss to check if a position should be exited based on adverse price movement.

  • 08

    Can I backtest this strategy?

    Yes, the get_historical_performance capability allows you to run the divergence strategy against historical snapshots to calculate the win rate.

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