SandboxAQ MCP Server

Overview

The Model Context Protocol (MCP) allows SandboxAQ to connect securely with large language models (LLMs) and AI assistants, enabling scientists and engineers to run high-accuracy molecular calculations conversationally and receive structured, traceable scientific results.

The SandboxAQ MCP Server exposes SandboxAQ's proprietary scientific AI models as callable tools within Claude and other MCP-compatible clients. This enables R&D teams to integrate molecular simulation directly into their existing AI-driven workflows without managing compute infrastructure.

What is the SandboxAQ MCP Server?

The SandboxAQ MCP Server is a standardized, managed connection framework that lets AI chat applications securely invoke SandboxAQ's proprietary scientific tools.

Through the MCP, users and agents can:

• Ask questions about molecular systems using natural language (e.g., "What is the most stable binding site for N₂ on a Co-Ni surface?").
• Retrieve structured scientific results — binding energies and relaxed geometries — formatted for immediate use in LLM reasoning.
• Run complex multi-step adsorption workflows without writing code or managing GPU infrastructure.
• Integrate SandboxAQ model outputs with other data sources, notebooks, or agentic pipelines.

The SandboxAQ MCP Server enables all model access to happens under SandboxAQ's security, authentication, and audit controls. No model weights or proprietary data are exposed externally.

How It Works

When a user submits an actionable query for the applicable SandboxAQ model through an LLM connected to the SandboxAQ MCP Server (for example, "Calculate the adsorption energy of CO on a copper 111 surface"), the MCP:

1. Parses the natural language input and maps it to the appropriate tool (aqcat).
2. Validates the request parameters and verifies the user's OAuth session.
3. Executes the calculation on SandboxAQ's managed GPU infrastructure using the AQCat Adsorption Spin model.
4. Returns a structured JSON response — including binding energies, relaxed structures, and metadata — to the LLM.
5. The LLM incorporates the scientific result into its response, answer, or downstream reasoning.

The entire compute lifecycle happens on SandboxAQ infrastructure.

Prerequisites

To access the SandboxAQ MCP Server through a compatible client, the following must be in place:

• An active SandboxAQ MCP Server tenant, provisioned at https://www.sandboxaq.com/.
• OAuth credentials — an email/password issued during sign-up, or a Google account for social login. Enterprise SSO via your organization's identity provider is optional and can be configured from the platform console.
• A supported MCP client: Claude Desktop, Claude Desktop UI (Pro or Enterprise), or any MCP-compatible application.

Using the SandboxAQ MCP Server

The SandboxAQ MCP Server can be used by any AI agent or LLM that supports the Model Context Protocol. This enables researchers, developers, and enterprise teams to invoke SandboxAQ's scientific AI models directly within their existing AI workflows while maintaining security and IP protection.

Example Scenarios

• LLM-Driven Research Assistant: Connect Claude to the SandboxAQ MCP Server to answer questions like "Which platinum surface facet binds hydrogen most weakly?" without any manual setup.
• Internal Copilot Integration: Embed the SandboxAQ MCP Server into another internal agent to enable scientific planning and post-analysis of adsorption workflows.
• Third-Party AI Platform: Integrate SandboxAQ model inference into another MCP-based AI platform under your organization's governance controls.

Setup Overview

1. Sign up: Provision your tenant at https://www.sandboxaq.com/. You'll receive your tenant-specific server URL and credentials, and can optionally configure SSO from the platform console. Enterprise customers with negotiated terms: contact mcp-prod@sandboxaq.com instead.
2. Configure Your MCP Client: Follow the client-specific instructions below to add your server URL.
3. Enter Your MCP URL: Your tenant-specific server URL is issued at sign-up and follows the pattern: https://mcp.{tenant}.aisim.sandboxaq.com
4. Authenticate: SandboxAQ MCP authentication is OAuth-based. Sign in with your email and password, or use Google social login. No API keys are issued or accepted. Enterprise tenants configuring SSO through their own identity provider — contact mcp-prod@sandboxaq.com.
5. Verify Connection: Once connected, ask Claude: "What tools does the SandboxAQ MCP Server provide?" — Claude should list the available tools and their descriptions.
6. Run Your First Query: Use any of the example prompts in the Usage Examples section below.

Claude Desktop UI (Remote MCP)

Navigate to Settings → Connectors → Add Connector and enter your tenant-specific server URL. Select OAuth as the authentication method and complete sign-in via your organization's SSO provider when prompted.

Claude Code (CLI)

Add the SandboxAQ MCP Server to Claude Code via the claude mcp add CLI command, or by editing your project's .mcp.json (or ~/.claude.json) directly.

// .mcp.json (project-scoped) or ~/.claude.json (user-scoped)
{
  "mcpServers": {
    "sandboxaq-mcp": {
      "type": "http",
      "url": "https://mcp.{tenant}.aisim.sandboxaq.com"
    }
  }
}

To authenticate after the server is configured:

1. Start Claude Code in your project directory (or any directory that inherits the user-scoped ~/.claude.json).
2. Open the MCP menu by running /mcp inside the Claude Code session. Select sandboxaq-mcp and choose Authenticate — Claude Code presents the option when the server requires auth.
3. Complete the OAuth handshake in the browser. Claude Code opens the SandboxAQ sign-in page. Sign in with your OAuth credentials (email + password, or Google social login). SandboxAQ does not issue or accept static API keys.
4. Verify. Back in the Claude Code session, re-run /mcp — the sandboxaq-mcp entry should now show as authenticated and list its available tools. As a functional check, prompt: "What tools does the SandboxAQ MCP Server provide?" Claude Code should enumerate aqcat and the four AQPotency tools.

Gemini CLI

Add the SandboxAQ MCP Server with gemini mcp add --transport http sandboxaq-mcp https://mcp.{tenant}.aisim.sandboxaq.com, or by editing your ~/.gemini/settings.json (or project-scoped .gemini/settings.json) directly. After editing, restart the CLI and run /mcp to confirm the server's tools are listed.

// ~/.gemini/settings.json (or .gemini/settings.json for project scope)
{
  "mcpServers": {
    "sandboxaq-mcp": {
      "httpUrl": "https://mcp.{tenant}.aisim.sandboxaq.com"
    }
  }
}

Antigravity

In the Antigravity IDE, open the Agent panel, click the ⋯ menu, then MCP Servers → Manage MCP Servers → View raw config to open mcp_config.json. Add the entry below, save, and click Refresh in the Installed MCP Servers list.

// ~/.gemini/config/mcp_config.json
{
  "mcpServers": {
    "sandboxaq-mcp": {
      "serverUrl": "https://mcp.{tenant}.aisim.sandboxaq.com"
    }
  }
}

Availability in Other MCP Clients

The SandboxAQ MCP Server is compatible with any client that supports the Model Context Protocol over Streamable HTTP transport. Point your client at your tenant-specific server URL and authenticate when prompted.

Hyperscaler Deployments

Hyperscaler deployment is an enterprise-only offering. Enterprise customers can connect to the SandboxAQ MCP Server through their existing hyperscaler footprint — Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) — for private networking, centralized billing, and identity integration. Self-serve tenants use the shared managed endpoint at https://mcp.{tenant}.aisim.sandboxaq.com instead.

Available Tools

The SandboxAQ MCP Server currently exposes one tool — aqcat — a read-only inference operation that performs no writes, modifications, or external side effects. Full parameter reference and schemas are documented on the AQCat Adsorption Spin page.

Usage Examples

The following example shows a realistic AQCat prompt you can use when the SandboxAQ MCP Server is connected to Claude, along with the expected output. For the full catalog of tool-triggering example prompts, see the AQCat → Example Prompts section and the AQPotency → Example Use Cases section.

Limits & Quotas

The following limits apply to all requests on the MCP endpoint. These are enforced server-side.

Pricing

The SandboxAQ MCP Server uses a per-Relaxation Unit (RU) billing model. One RU represents a single bulk–facet–adsorbate computation up to the maximum step limit.

Detailed usage logs (timestamp, organization, molecule count, compute duration) are available upon request for billing reconciliation.

For enterprise accounts and volume pricing, contact mcp-prod@sandboxaq.com.

Troubleshooting

Troubleshoot connection issues

If you're having trouble connecting to a service, try these steps:

1. Check that you have a stable internet connection.
2. Verify you have the right SandboxAQ-provided MCP URL.
3. Review any permissions or account type requirements for the service.
4. If authentication fails, try disconnecting and reconnecting from Settings → Connectors → Add Connector.

Desktop App Showing 'Disconnected' After Successful Web Authentication

After disconnecting and reconnecting the SandboxAQ MCP Server from Claude Desktop, the Anthropic authorization popup may confirm the connection succeeded while the Claude Desktop app continues to display the connector as not connected. This is a known Claude Desktop UI-refresh delay — the underlying OAuth handshake completed successfully; the desktop client just failed to pick up the new state.

If the toggle doesn't clear it, sign out of Claude Desktop and sign back in. Fully signing out and back in forces the desktop client to re-fetch its connector state and the active tool list, at which point the SandboxAQ MCP Server will show as connected. Simply quitting and reopening the app is not always sufficient.

If the connector still shows as disconnected after signing back in, remove the connector entirely from Settings → Connectors, then re-add it via Add Connector using your SandboxAQ-provided MCP URL.

Improving tool-invocation reliability

Large language models are non-deterministic when deciding whether to invoke an MCP tool. Even when a prompt clearly maps to a SandboxAQ MCP tool (aqcat, AqpotencyPotency, AqpotencyScreen, AqpotencyScan, AqpotencySelectivity), the model may occasionally answer from its own knowledge instead of calling the tool. The recommendations below make tool invocation substantially more consistent. The setup differs by client: Claude Desktop exposes a UI toggle; Claude Code requires an environment variable.

# Shell (bash / zsh) — export before launching Claude Code
export ENABLE_TOOL_SEARCH=true

# Or add to the server entry in .mcp.json / ~/.claude.json:
#   "sandboxaq-mcp": {
#     "type": "http",
#     "url": "https://mcp.{tenant}.aisim.sandboxaq.com",
#     "env": { "ENABLE_TOOL_SEARCH": "true" }
#   }

Prompt-phrasing tips that reliably trigger the correct tool:

• Name the tool explicitly. Prefer "Use the AQCat tool to calculate the binding energy of N₂ on Co-Ni (111)" over "What is the binding energy of N₂ on Co-Ni (111)?"
• Include the required parameters up front. For AQCat: bulk composition, adsorbate, and facet. For AQPotency: SMILES and UniProt ID (or panel name).
• Ask a scoped, computational question rather than an open-ended one. "Screen these 500 SMILES against P00533 with AqpotencyScreen" triggers the tool more reliably than "Which of these compounds bind EGFR?"
• Point at the SandboxAQ MCP Server by name when a session has multiple MCP servers connected — the model otherwise weighs across all available tools.
• If the model still doesn't call the tool, explicitly ask it to. "Please call the aqcat tool with the parameters above" is a valid recovery prompt.

If the issue persists, contact support.aisim@sandboxaq.com.

Permissions & Security

MCP queries run on behalf of the authenticated user, verified via OAuth 2.0. All compute runs on SandboxAQ-managed infrastructure — model weights are not transmitted to or accessible by end users.

• IP Protection: Model weights are encrypted and not exposed via the MCP interface. All inference occurs within SandboxAQ's secure compute environment.
• OAuth 2.0: Authentication is handled through OAuth — email/password, Google social login, or enterprise SSO via your organization's identity provider. No API keys are issued or stored.
• Organizational Isolation: Each organization's requests and usage data are isolated to prevent cross-organization data access.
• Enterprise VPC deployment: High-security enterprise clients may request deployment of the AQCat inference stack within their own VPC, providing zero-data-egress capabilities. This is an enterprise-only offering — contact mcp-prod@sandboxaq.com to scope a customer-VPC deployment.

Privacy & Data

See the SandboxAQ Privacy Policy and the Data Protection Addendum for full details on how SandboxAQ collects, uses, and protects data related to your use of the MCP Server.

Support

SandboxAQ will use commercially reasonable efforts to meet or exceed an uptime of 99.9% for Hosted Services.

Support Hours

Severity & First-Response Targets

Updates

Bug fixes and point releases are included at no additional charge when generally made available to other customers.