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Security & Compliance

Securing OAuth API Access for LLMs: The MCPify Gateway Approach

Securely connect GPT-5, Claude to OAuth-protected APIs with MCPify's LLM gateway. Learn OAuth vault, automatic refresh, scope control, and monitoring for 100+ APIs.

Herman Sjøberg
Herman Sjøberg
AI Integration Expert
August 14, 20258 min read
OAuth 2.0OAuth 2.1LLM SecurityMCPAPI GatewayEnterprise Security

Key Takeaways

  • Encrypted OAuth vault with automatic token refresh
  • Scope-aware tools with least-privilege enforcement
  • Rate limiting, caching, and full audit logs
  • 100+ pre-integrated APIs (Slack, HubSpot, Stripe, etc.)
  • Prevents secrets from appearing in prompts or logs
  • Multi-API autonomous workflow capabilities
  • Secure LLM API gateway
  • GPT OAuth API integration
  • AI access to Google API

Enabling OAuth-Protected API Access for LLMs with MCPify

TL;DR: OAuth is the right way to grant LLMs access to user data in SaaS apps—but it's hard to do safely. MCPify is a secure, multi-tenant AI gateway that turns any OAuth-backed API into an MCP tool with zero code. It provides an encrypted OAuth vault, automatic refresh, granular scope control, rate limiting, and full audit logs—so GPT, Claude, and other agents can call real APIs safely.

Why OAuth is Hard for AI Agents

Connecting an AI agent to a protected API isn't as simple as handing it a key. OAuth 2.0/2.1 uses browser redirects, code exchanges, short-lived access tokens, and long-lived refresh tokens. Those flows don't map cleanly into a chat loop, and rolling your own token storage/refresh is risky and brittle.

Even after you complete the grant, secrets must never live in prompts or logs. Store tokens in an encrypted vault on the server and inject them only at call time; otherwise you risk accidental exposure (and real-world attacks show secrets do leak).

Finally, least-privilege matters. If an agent has broad scopes, a prompt-injection or misinterpretation can lead to unintended destructive calls ("Excessive Agency"). Your gateway must constrain scopes, sanitize inputs, and provide guardrails.

Bottom line: You need a purpose-built gateway that handles OAuth flows, encrypts and refreshes tokens automatically, enforces scopes, and mediates every call.

Meet MCPify: A Secure LLM API Gateway for OAuth

MCPify is a multi-tenant gateway that instantly converts any API into an MCP service (works with Claude, ChatGPT, and any MCP-compatible assistant). You upload a config or spec; MCPify handles the rest:

  • Zero-code OAuth handling — Bring your API credentials, click through consent, and you're done.
  • Encrypted OAuth vault + auto-refresh — Access/refresh tokens stored securely; refreshes happen behind the scenes.
  • Scope-aware tools — Expose only allowed endpoints; block out-of-scope actions by design.
  • Rate limiting, caching, analytics — Production-ready controls, centralized logs, usage metrics.
  • Gateway-first, multi-tenant — One gateway hosts 100+ APIs already MCPified; add your own in minutes.

See the Architecture and Getting Started docs for the specifics on the OAuth vault, auto-refresh, token counting, and rate limiting.

Standards note: MCP servers can be protected; clients/connectors pass tokens when invoking tools. With the MCP connector, you supply an authorization token—token acquisition/refresh is handled by your gateway (e.g., MCPify).

What This Enables (Real Use Cases)

1) Calendar Copilot (Google Calendar via OAuth)

Ask: "Find 30 minutes with Alex next week and send an invite."
MCPify exposes read/write-scoped Calendar endpoints as tools. The agent lists free slots and creates an event—without ever seeing the raw tokens. You can keep it read-only by removing write tools.

2) CRM Sidekick (Salesforce)

"Show ACME's pipeline and add a note to the opportunity."
Grant minimal CRM scopes; enable GET for read paths and select POST for notes only. MCPify enforces scope and tool allow-lists so the agent can't escalate to destructive actions.

3) Notion Knowledge Navigator

"Find the onboarding doc for Project X and summarize the action items."
OAuth to Notion once; the agent uses searchPages and getPageContent tools. Large responses are chunked, cached, and navigated with JSON query tools—saving tokens and time.

4) Multi-API Autonomous Workflows

New deal closes in Salesforce → create a project board (Trello), schedule a kickoff (Calendar), send a welcome email (Gmail). One MCPify gateway mediates all API calls with centralized scopes, logs, and rate limits.

How MCPify Tackles the OAuth Headaches

  • Initial grant handled outside the chat loop
    MCPify guides the user through the consent screen once. Tokens are stored server-side in an encrypted vault under your project.

  • Automatic refresh & expiry management
    Access tokens expire; MCPify refreshes them automatically using the stored refresh token. Your agent just calls tools—no "my token expired" errors.

  • Granular scope & endpoint exposure
    You decide which endpoints become tools. MCPify enforces least privilege and blocks out-of-scope calls.

  • Sanitization, rate limits, and audit logs
    Every call passes through the gateway for validation, global rate limiting, and full auditability—crucial for compliance and safety.

  • 100+ APIs, one gateway
    Use pre-integrated services (Slack, HubSpot, Stripe, GitHub, Salesforce, Notion, Airtable, Discord, and more) or bring any OpenAPI/GraphQL/SOAP service.

Quick Start (3 Minutes)

  1. Create an account: Go to mcpify.org/auth/register and spin up your gateway.
  2. Add a service: In Docs → Getting Started, follow the "Create Configuration" step to register your API (or choose a pre-integrated service).
  3. Authorize (OAuth): Click Connect → complete the consent screen → tokens land in MCPify's encrypted vault.
  4. Select tools & scopes: Expose only the endpoints you want the agent to use.
  5. Connect your LLM: Point Claude, ChatGPT, or your agent framework at your MCPify service URL (MCP tools are auto-described with schemas).
  6. Monitor & iterate: Use built-in analytics and logs to tune scopes, batch/parallelize calls, and optimize token usage.

Pricing & plans: Start free, then scale with Pro or Enterprise (SSO, audit logs, self-hosted options).

Implementation Tips & Guardrails

  • Use the smallest set of scopes needed for the task ("read calendar" vs. "full access").
  • Separate read and write tools so prompts can't mix intentions.
  • Validate inputs for tool calls (IDs, dates, amounts).
  • Watch for injection: keep high-risk operations behind confirmations.
  • Log & alert on unusual call volumes or repeated failures.

FAQ

Is this compliant with MCP?
Yes. MCPify presents your APIs as MCP tools with formal JSON schemas and auth requirements. Agents interact via the standardized MCP protocol.

Who owns the tokens?
You do. MCPify stores them encrypted in your project's vault; the LLM never sees raw tokens.

Can I bring my own OAuth app?
Yes. Configure your client ID/secret and redirect URI in the MCPify dashboard; MCPify performs the grant and manages refresh.

What about non-OAuth APIs?
API keys and other auth types are supported. You still get caching, token counting, pagination, chunking, analytics, and guardrails.

Call to Action

Give your LLM secure superpowers in minutes—without writing OAuth code.

Sources

Who This Article Is For

Enterprise security teams and architects building secure AI agent systems

About the Author

Herman Sjøberg

Herman Sjøberg

AI Integration Expert

Herman excels at assisting businesses in generating value through AI adoption. With expertise in cloud architecture (Azure Solutions Architect Expert), DevOps, and machine learning, he's passionate about making AI integration accessible to everyone through MCPify.

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