AI Agent Trust & Governance
Arcade vs Workato: which supports multi-user “act on behalf of user” permissions plus SSO/RBAC for an agent product?
8 min read
When you’re building an agent product that has to “act on behalf of” many different end users, generic workflow automation breaks down fast. The core question stops being “Can I hit the API?” and becomes: “Can I safely execute actions with each user’s own permissions, wired into my SSO/RBAC model, without rebuilding auth for every integration?”
Quick Answer: Arcade is built specifically for multi-user, “act as the user” authorization with SSO/RBAC and user-scoped OAuth for agents. Workato can automate workflows across systems but is primarily service-account and recipe–centric, which makes true per-user delegation for agent products much harder to implement and govern.
Frequently Asked Questions
How do Arcade and Workato differ for multi-user, “act on behalf of user” agents?
Short Answer: Arcade is an MCP runtime designed so agents act with user-specific permissions (not service accounts), while Workato is a workflow automation platform optimized for recipes and shared connections, not multi-user agent delegation.
Expanded Explanation:
If you’re shipping an AI agent where each user’s actions must reflect their own identity and scopes (e.g., “send email as Alice,” “create calendar event on Bob’s calendar”), you need first-class support for user-specific OAuth and a governance layer that aligns with your SSO/RBAC model. Arcade is built around that assumption: it provides Secure Agent Authorization so each tool call runs under a specific user’s identity, with OAuth and IDP flows integrated into the runtime and no tokens exposed to the LLM.
Workato, by contrast, excels at building workflow recipes that run under shared or admin-level connections. You can sometimes simulate per-user behavior with multiple connections, but the platform’s mental model is “automations owned by a workspace,” not “agents acting as hundreds or thousands of distinct users.” That mismatch shows up when you try to wire a chat-based agent to take user-specific actions reliably and safely at scale.
Key Takeaways:
- Arcade is built for multi-user agent authorization and user-scoped actions; Workato is built for recipe-based automation using shared connections.
- For an agent product, Arcade’s per-user permission model and tool runtime map directly to “act on behalf of” use cases; Workato generally requires workarounds and still leans on service-account style access.
What does the implementation process look like for multi-user, user-scoped permissions?
Short Answer: With Arcade, you integrate once with its MCP runtime and auth APIs, then every agent action runs under a specific user’s identity; with Workato, you typically juggle multiple connections and recipes, and still don’t get a native “agent runtime” abstraction.
Expanded Explanation:
In Arcade, the implementation path is: plug your agent into Arcade’s MCP runtime, call auth.start to kick off OAuth or SSO flows per user, and then let your agent call tools (e.g., Google.SendEmail, Google.CreateEvent) that execute with that user’s permissions. The runtime handles token persistence and refresh, enforces scopes, and keeps secrets out of the model.
In Workato, you’re usually designing recipes that are triggered by events, schedules, or API calls. To approximate per-user behavior, you might create separate connections per user or per group and then dynamically route work to the right recipe or connection. It’s workable for some internal automation, but brittle and operationally heavy when the surface area is “agent calls arbitrary tools for thousands of end users via chat.”
Steps:
- With Arcade:
- Sign up for Arcade and install the SDK.
- Use
client.auth.start(user_id, "google")(or similar) to kick off OAuth for each user. - In your agent, call Arcade MCP tools (e.g.,
Gmail.ListEmails,Google.SendEmail) that automatically run with that user’s tokens.
- With Workato:
- Define recipes and connections to each system (Gmail, Slack, CRM, etc.).
- Decide how to model per-user access (e.g., separate connections, folders, roles).
- Build an integration layer between your agent and Workato’s API or webhook triggers, then route calls to the right recipe/connection.
- Operationalize:
- Arcade: monitor agent actions and tool usage via Arcade’s runtime, audit logs, and governance controls.
- Workato: monitor recipe runs, handle connection failures/rotations, and manage connection sprawl for each user or group.
How do Arcade and Workato compare on SSO, RBAC, and enterprise governance?
Short Answer: Both support enterprise controls, but Arcade’s SSO/RBAC model is designed to govern agent tools and per-user authorization, whereas Workato’s RBAC is tuned for who can edit/run recipes and use shared connections.
Expanded Explanation:
In a production agent, SSO and RBAC aren’t just about who can log into the admin console; they’re about whose identity the agent is allowed to impersonate and which tools it can use on their behalf.
Arcade integrates with your existing OAuth and IDP flows so that when a user authenticates (via SSO or OAuth), the runtime binds their identity to specific tools and scopes. RBAC controls which agents and tools are available to which users and teams, and every tool call is logged for auditability. The emphasis is: “Agents act with user-specific permissions—not service accounts,” with tenant isolation, audit logs, and SSO/SAML controls backing that up.
Workato offers SSO and RBAC for the platform itself: who can create/modify recipes, who can manage connections, and how environments are segmented. That’s essential for an automation platform, but the authorization boundary is around recipe ownership and shared connectors, not around multi-user agent tool execution and per-call impersonation of different end users.
Comparison Snapshot:
- Arcade: SSO/RBAC govern which agents/tools can act for which end users, with user-specific OAuth and “zero token exposure to LLMs” as core design constraints.
- Workato: SSO/RBAC mainly protect who can access the Workato workspace, manage recipes, and use shared connections.
- Best for:
- Arcade: agent products that must safely act as many different users across systems (Gmail, Calendar, Slack, GitHub, Salesforce, HubSpot, Linear, etc.).
- Workato: centralized workflow automation and integrations owned by an ops or IT team.
How do I actually wire an AI agent into Arcade or Workato?
Short Answer: With Arcade you plug your agent directly into an MCP runtime and call tools; with Workato you orchestrate between your agent and Workato’s recipes via APIs/webhooks, treating Workato as a downstream automation engine.
Expanded Explanation:
Arcade positions itself as “the runtime between AI and action.” Your agent (running in Cursor, Claude, LangGraph, or your own stack) talks MCP, and Arcade provides the tools and auth. You don’t expose tokens to the model; you simply describe tools like Google.SendEmail or Slack.PostMessage in the agent’s tool schema, and Arcade executes them with the correct user’s permissions. The open-source MCP framework lets you build custom tools with OAuth and evals built-in, then deploy them with managed config and secrets.
Workato doesn’t speak MCP and isn’t an agent runtime. You’d expose Workato recipes via HTTP endpoints or APIs, then teach your agent to call those endpoints with the right payloads. Workato executes the recipe using the connection tied to it. This creates an extra translation layer: tools in your agent schema don’t map 1:1 to user-scoped actions; they map to Workato recipes that typically run under shared workspace credentials.
What You Need:
- Arcade:
- An MCP-compatible agent stack (Claude, Cursor, LangGraph, etc.).
- Arcade SDK (
arcadepyor JS) to handleauth.start,wait_for_completion, and tool calls.
- Workato:
- Access to Workato with appropriate connectors and recipes configured.
- A custom integration layer from your agent to Workato (HTTP, API, or SDK) plus a strategy to map agent intents to the right recipes and connections.
Strategically, when should I choose Arcade over Workato for an agent product?
Short Answer: Choose Arcade when your primary goal is a multi-user agent that can safely take actions as each user across many systems; choose Workato when your main need is centralized workflow automation, not an agent runtime.
Expanded Explanation:
If your product vision is “From chat to action in 7 minutes”—an agent that can read a customer’s inbox, draft and send follow-ups, create events on their calendar, update CRM records, and notify the team in Slack—all as the logged-in user, the limiting factor isn’t LLM reasoning. It’s auth, authorization, and tool reliability at scale.
That’s the exact problem Arcade is built to solve:
- Secure Agent Authorization with user-specific permissions, not service accounts.
- OAuth and IDP flows integrated into the runtime, so you’re not hand-rolling token storage/refresh for every integration.
- Agent-optimized tools (not just API wrappers) for Gmail, Google Calendar, Slack, Linear, GitHub, HubSpot, Salesforce, and more.
- Governance: tenant isolation, audit logs, RBAC, SSO/SAML, and deployment options from cloud to VPC, on-prem, or fully air-gapped.
Workato is excellent when you want a centralized team to orchestrate workflows across systems with recipes. But for an agent product where every end user expects “this behaves exactly like me clicking the UI,” and your security team expects strong authorization boundaries, user-level scopes, and clear audit trails tied to the agent, Arcade is the better strategic fit.
Why It Matters:
- Your agent is only as trustworthy as its authorization model; per-user OAuth + SSO/RBAC aligned to agents and tools is non-negotiable in production.
- Service-account bots and generic automation can get you through a demo, but they rarely survive security review or real-world multi-user complexity.
Quick Recap
For a multi-user agent that needs to “act on behalf of” each user across Gmail, Calendar, Slack, GitHub, CRMs, and more, you need a runtime that treats authorization, OAuth, and tool execution as first-class concerns. Arcade is that MCP runtime: it gives agents user-specific permissions, integrates with your existing OAuth/SSO/RBAC model, keeps tokens out of the model, and ships agent-optimized tools you can rely on at scale. Workato remains a strong choice for recipe-based workflow automation, but it’s not designed as an agent runtime and leans on shared connections and service-account patterns that don’t map cleanly to multi-user agent products.