Swiss Cheese AI (SCAI)

npx add-mcp 'https://www.swisscheeseai.com/api/mcp'

See SCAI work inside ChatGPT.

Stay in the conversation you already use. Ask ChatGPT to call SCAI, let the model council challenge the answer, and receive one integrated conclusion in the same chat.

Real SCAI connector workflow in ChatGPT

00 / Orientation

Your assistant stays the interface. SCAI joins as the review layer.

Model Context Protocol gives an AI host a standard way to call an external tool. With SCAI connected, you can send a prompt or an existing answer to an AI council without moving the conversation to another tab.

01

Keep your context

Work from the Claude, ChatGPT, Perplexity, or Gemini conversation that already contains your research.

02

Call the council

Ask the host to use SCAI. The connector starts a structured multi-model debate on your behalf.

03

Receive one answer

The integrated conclusion returns to the host, with the strongest reasoning and remaining uncertainty made clear.

00.5 / Connector, decoded

One chat. One handoff. More perspectives.

MCP is the bridge—not a new place to work. Your AI host keeps the conversation, sends only the context you approve to SCAI, and receives the council's integrated answer.

01 / Context stays in the chat Start where the work already is. In ChatGPT or another supported host, approve the SCAI tool call. MCP carries the relevant request—no copy-and-paste detour.

02 / Approved context goes to SCAI SCAI gets the assignment. The host sends the approved context through the connector, so the SCAI council can generate, challenge, and compare perspectives on the same question.

03 / Integrated answer returns Prompt in. Debate. Stronger answer out. SCAI returns one integrated result through MCP. Your original host presents it in the same conversation, with the flow and context intact.

01 / Setup

Choose your AI app. Follow the connector flow.

Each guide uses the same SCAI endpoint. Setup usually takes a few minutes. Availability can depend on your plan, workspace settings, region, and each host's current rollout.

Connector 02

ChatGPT

MCP custom connector ChatGPT setup through a custom app.

Plan access may vary

https://www.swisscheeseai.com/api/mcp

1. Copy the SCAI MCP URL shown above.
2. In ChatGPT, open Settings → Apps → Advanced settings and enable Developer mode if your plan or workspace requires it.
3. Return to Apps, choose Create, name the custom app “SCAI”, and paste the MCP server URL.
4. Complete the Swiss Cheese AI sign-in and consent flow, then connect the app. Workspace users may need an admin to allow custom apps.
5. Enable SCAI from ChatGPT's tools or apps menu, then ask: “Use SCAI to debate this answer and give me the integrated conclusion.”

OpenAI may label MCP integrations “apps” rather than “connectors.” The setup still points ChatGPT to SCAI's hosted Model Context Protocol endpoint.

02 / MCP protocol tutorial

What happens after you press Connect?

This remote MCP server example keeps the host as your interface. SCAI exposes its council as a tool, receives the approved request, runs the debate, and returns the result.

1. 01 Your AI host receives a prompt Claude, ChatGPT, Perplexity, or Gemini Spark
2. 02 The host discovers SCAI tools Through the remote MCP endpoint
3. 03 You approve the agent tool call Consent and tool permissions stay visible
4. 04 The AI council debates Generate → evaluate → integrate
5. 05 The result returns to the host Continue in the conversation you started

03 / Authentication

Connected deliberately. Not silently.

SCAI uses the security flow supported by each host. You can inspect the requested access, approve the first tool call, and disconnect the integration from your host settings.

OAuth 2.1 / PKCE

Bound to the client

This MCP server with OAuth PKCE example avoids placing a reusable secret in the browser. PKCE binds authorization to the client that began it.

Registration

No hand-entered ID

Claude can use MCP dynamic client registration. Leave OAuth Client ID and Client Secret blank and let the connector register itself.

Consent

Review before allowing

The MCP consent screen example shows requested access before connection, including debates, available SCAI resources, and credit use.

Not another single-model answer.

SCAI is an AI council: a structured AI debate tool that uses different model roles to propose, challenge, and integrate an answer. It can act as an AI panel of experts and an AI panel review without pretending that disagreement is the same as truth.

Use it for cross-model AI verification, multi-model AI consensus, or a second opinion when the cost of an unchecked assumption is high. The goal is stronger scrutiny—not a cosmetic AI answer confidence score.

If you are comparing a Perplexity alternative, Consensus AI alternative, You.com alternative, or the best AI for accurate answers, SCAI takes a different position: it is an AI tool that uses multiple models inside the assistant you already chose.

1. 01 Generator Builds the strongest initial answer and makes its assumptions explicit.
2. 02 Evaluator Tests gaps, contradictions, unsupported claims, edge cases, and risks.
3. 03 Integrator Resolves the debate into one useful conclusion with uncertainty visible.

04 / Where SCAI fits

Research tool, replacement, or review layer?

SCAI is most useful as a review layer inside the assistant you already prefer. These comparisons answer different questions—not interchangeable product categories.

SCAI vs Perplexity

Use Perplexity for research; call SCAI when you want several models to challenge and integrate the answer. The MCP connector lets both workflows coexist.

SCAI vs Consensus AI

Separate source discovery from cross-model debate. SCAI's defining feature is its generator–evaluator–integrator council.

Claude vs ChatGPT for research

Connect SCAI to either supported host and run the same council from the interface and context you prefer.

SCAI vs council-ai

Compare host support, model roles, consent, history, and pricing against your workflow rather than relying on a generic “best” label.

05 / MCP connector FAQ

Before you connect.

Practical answers about support, authentication, credits, and what a multi-model review can—and cannot—prove.

What is the SCAI MCP custom connector?

It is a hosted remote Model Context Protocol server that exposes Swiss Cheese AI's council as tools. A supported AI host can call SCAI, run a multi-model debate, and bring the integrated result back into your original conversation.

How do I add the MCP server to Claude, ChatGPT, or Perplexity?

Use the platform guide above to add MCP server to Claude, add MCP server to ChatGPT, or add MCP server to Perplexity. Each flow starts with the same SCAI endpoint, then uses the host's custom connector or custom app settings.

Which apps can add the SCAI MCP server?

This page covers Claude, ChatGPT, Perplexity, and Gemini Spark beta. Support can vary by subscription, workspace policy, region, and the current feature rollout in each host.

Do I need an OAuth client ID or client secret?

Not in Claude: leave both fields blank. SCAI supports dynamic client registration, which lets the host register itself during the OAuth flow. Follow the platform-specific authentication instruction for other hosts.

Do MCP debates use SCAI credits?

Yes. Debates launched through a connector use your SCAI credits and appear in your SCAI history with the source host identified.

Does multi-model consensus guarantee an AI verified answer?

No. Independent critique can expose more blind spots than an unchecked response, but an AI verified answer is not a guarantee of truth. Verify medical, legal, financial, safety-critical, and other high-stakes outputs with qualified sources.

How can I fact-check ChatGPT or reduce AI hallucinations?

Add SCAI to ChatGPT and ask it to debate the answer. The evaluator looks for weak assumptions and conflicts; the integrator produces a revised conclusion with uncertainty. This supports AI hallucination detection, how to reduce AI hallucinations, and how to fact-check ChatGPT—but primary evidence still matters.

Is ChatGPT accurate, and should I trust AI answers?

Accuracy depends on the question, context, model, tools, and evidence. Treat every AI answer as a claim to assess—not automatic truth. Primary sources and qualified human review remain essential when the cost of error is high.

Is SCAI a stateless MCP server?

SCAI is a hosted remote MCP service, so you do not configure transport state yourself. Your account, consent, debate history, and credits are handled by the service while the host uses its supported MCP transport.