Keep your context
Work from the Claude, ChatGPT, Perplexity, or Gemini conversation that already contains your research.
Swiss Cheese AI / MCP connection guide
A second opinion, inside the AI you already use.
Connect Claude, ChatGPT, Perplexity, or Gemini Spark to Swiss Cheese AI. One hosted MCP endpoint brings SCAI's multi-model debate into the conversation already on your screen.
SCAI MCP endpoint
https://www.swisscheeseai.com/api/mcp
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.
Call the council
Ask the host to use SCAI. The connector starts a structured multi-model debate on your behalf.
Receive one answer
The integrated conclusion returns to the host, with the strongest reasoning and remaining uncertainty made clear.
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 01
Claude
MCP custom connector Claude setup for the web app or Claude Desktop.
OAuth 2.1 + PKCEhttps://www.swisscheeseai.com/api/mcp
- Copy the SCAI MCP URL shown above.
- In Claude—claude.ai or Claude Desktop—go to Settings → Connectors → Add custom connector.
- Name it “SCAI”, paste the URL as the Server URL, leave OAuth Client ID and Client Secret blank, then press Add.
- Claude opens the Swiss Cheese AI consent screen. Sign in if needed, review the requested permissions, then press Allow.
- Back in Claude, approve the tool permission on first use. Ask Claude to “use SCAI” or “run a Swiss Cheese debate.”
Looking for an MCP custom connector with no client ID? SCAI uses dynamic client registration on supported OAuth hosts, so Claude does not need credentials configured by hand.
Connector 02
ChatGPT
MCP custom connector ChatGPT setup through a custom app.
Plan access may varyhttps://www.swisscheeseai.com/api/mcp
- Copy the SCAI MCP URL shown above.
- In ChatGPT, open Settings → Apps → Advanced settings and enable Developer mode if your plan or workspace requires it.
- Return to Apps, choose Create, name the custom app “SCAI”, and paste the MCP server URL.
- Complete the Swiss Cheese AI sign-in and consent flow, then connect the app. Workspace users may need an admin to allow custom apps.
- 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.
Connector 03
Perplexity
MCP custom connector Perplexity setup for a second opinion inside research.
Custom connectorhttps://www.swisscheeseai.com/api/mcp
- Copy the SCAI MCP URL shown above.
- In Perplexity, go to Settings → Connectors → Add custom connector.
- Name it “SCAI”, paste the URL as the Server URL, then press Add.
- Perplexity opens Swiss Cheese AI. Sign in if needed, review the consent screen, and press Allow.
- Back in Perplexity, approve the tool permission on first use. Ask for a “second opinion” or a “Swiss Cheese debate.”
Perplexity can remain your research interface; SCAI adds a generator–evaluator–integrator review without replacing that workflow.
Connector 04
Gemini Spark
Gemini Spark MCP connector setup through Connected Apps.
Betahttps://www.swisscheeseai.com/api/mcp
- Reveal your MCP URL above and copy it.
- Go to gemini.google.com, then Settings → Connected Apps.
- Choose Add custom connected app and paste the URL.
- In Advanced settings, set Authentication to “None.”
- Tick the risk acknowledgement, press Connect, then Continue.
Gemini Spark support is beta. Interface labels, access, and authentication options may change during Google's rollout.
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.
- 01Your AI host receives a promptClaude, ChatGPT, Perplexity, or Gemini Spark
- 02The host discovers SCAI toolsThrough the remote MCP endpoint
- 03You approve the agent tool callConsent and tool permissions stay visible
- 04The AI council debatesGenerate → evaluate → integrate
- 05The result returns to the hostContinue 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.
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.
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.
Review before allowing
The MCP consent screen example shows requested access before connection, including debates, available SCAI resources, and credit use.
The product behind the connector
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.
- 01GeneratorBuilds the strongest initial answer and makes its assumptions explicit.
- 02EvaluatorTests gaps, contradictions, unsupported claims, edge cases, and risks.
- 03IntegratorResolves 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.