Arcade AI
PaidThe MCP runtime for secure, production-ready AI agents
By Tanmay Verma, Founder · Last verified 03 Jun 2026
6.6k views
Added 9d ago
80/100Safe BetThe MCP runtime for secure, production-ready AI agents
By Tanmay Verma, Founder · Last verified 03 Jun 2026
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Arcade fills a critical gap for teams wanting to deploy AI agents that take actions on behalf of users. Its secure OAuth handling and pre-built MCP tools reduce time to production, but it's best suited for organizations already using or planning to use MCP. If you're not on MCP, the ecosystem lock-in is worth considering.
Last verified: June 2026
Arcade squarely addresses the 'last mile' problem of AI agents: taking real actions on behalf of users without security nightmares. Its standout feature is the seamless OAuth flow that ties agent actions to individual user permissions, not service accounts. This is a massive win for compliance-minded teams. The pre-built MCP tools catalog (Google, Slack, Salesforce, X) accelerates development, and the ability to deploy in your VPC or air-gapped adds enterprise credibility. However, this comes with a tight coupling to the MCP ecosystem — if your stack isn't MCP-native, adoption requires buy-in. Also, the runtime is a new layer; teams must evaluate if the added abstraction outweighs direct API integration. For teams building multi-user agents that need to access user data across SaaS platforms (e.g., a CRM bot that reads emails and updates deals), Arcade is a clear time-saver. But if your agents only need internal or read-only data, simpler solutions may suffice. The documentation emphasizes Python and JavaScript SDKs, indicating a developer-first approach, but non-technical admins might find the governance dashboard learning curve steep. Compared to alternatives like building your own auth middleware or using generic AI frameworks, Arcade's focus on MCP and production auth gives it a distinct edge for secure action-taking agents.
Skip Arcade AI if Skip Arcade if you are a hobbyist building a simple chatbot with no need for multi-user authorization or third-party service integrations.
Outlines six signs that DIY agent plumbing needs an MCP runtime for identity, policy, audit, and reuse.
Arcade MCP Gateways now integrate with existing SSO for org-wide agent deployments.
How likely is Arcade AI to still be operational in 12 months? Based on 6 signals including funding, development activity, and platform risk.
Arcade is an MCP (Model Context Protocol) runtime designed to make AI agents production-ready by handling authorization, reliability, and governance. It targets teams deploying multi-user agents that take actions across business systems like Google, Slack, Salesforce, and X (Twitter). Key features include secure agent authorization with user-specific permissions and integration with existing OAuth and IDP flows, an agent-optimized tools catalog with high-quality MCP tools built for reliability and cost-efficiency, an MCP framework for building custom tools with OAuth and evals built-in, and deployment flexibility across cloud, VPC, on-premises, or air-gapped environments. Arcade also provides agent lifecycle governance for control over tools and agents. Compared to building custom MCP infrastructure, Arcade offers a drop-in runtime that simplifies OAuth, token management, and scaling, as highlighted by users such as Harrison Chase (LangChain) and Snyk's security team.
Tell us what you want to build — we'll match the AI tools that fit your goal, budget & existing stack.
Concrete scenarios for the personas Arcade AI actually fits — and what changes day-one when you adopt it.
You need to deploy an AI agent that reads customer account data from Salesforce and sends personalized emails via Gmail, but only after the customer consents per session.
Outcome: Using Arcade's user challenges and per-user OAuth, you enforce user-specific scope approval for each tool call, avoiding shared service accounts while maintaining audit trails.
Your bot needs to query Slack message history, create Jira tickets, and post updates—all on behalf of the support agent who invoked it.
Outcome: Arcade's MCP runtime handles auth delegation for each Slack workspace, and the built-in tool catalog (Slack, Jira via custom tool) enables quick integration without custom OAuth code.
You're standardizing how multiple AI agents access Google Workspace and Salesforce across departments, with RBAC and audit logging required.
Outcome: Arcade Enterprise provides dedicated tenant isolation, SSO/SAML, RBAC roles, and compliance-ready audit logs, allowing you to govern all agent tool calls from a central console.
Rate limit of 1,000 requests per minute; free tier limited to 100 user challenges and 1,000 standard tool executions; pro tool executions are more expensive ($0.50 each after 100 on Growth); enterprise features like audit logs and RBAC require custom pricing; no on-premise deployment option; scheduled tool executions incur additional cost ($0.005 per execution).
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
For each published Arcade AI tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Hobby
$0/mo
Ideal for
Individual developers prototyping AI agents with low-volume tool calls, up to 100 auth challenges and 1,000 standard executions.
What this tier adds
Free entry point with 1 hosted MCP server, limited to community support via GitHub.
Growth
$25/mo + usage
Ideal for
Small teams deploying agents to production with moderate usage, needing email support and SLA.
What this tier adds
Adds 600 included user challenges, 2,000 standard executions, 100 pro executions, and hourly MCP server billing at $0.05/hour; overage charges apply.
Enterprise
Custom
Ideal for
Large organizations requiring audit logs, RBAC, SSO/SAML, dedicated infrastructure, and custom compliance.
What this tier adds
The company stage and team size where Arcade AI's pricing actually pencils out — and where peers do it cheaper.
Arcade's usage-based pricing (no seat licenses) benefits teams with sporadic agent usage. The free Hobby tier is sufficient for prototyping, but growth teams quickly hit execution limits. At $25/mo, Growth is competitive with alternatives like Runloop or CopilotKit for low-volume use, but overage costs can escalate if agents are heavily used. Enterprise custom pricing is typical for compliance-heavy deployments. For very high-volume, dedicated agents, a flat-rate platform might be cheaper.
How long it actually takes to get something useful out of Arcade AI — broken out by persona, not the marketing-page minute.
For a simple agent with pre-built tools (e.g., Google.SendEmail): ~15 minutes if you already have an API key. Custom tool development via SDK adds a few hours. Enterprise SSO and RBAC configuration may take a day. Hosted MCP servers spin up in minutes.
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
Pricing, brand, ownership, or deprecation changes worth knowing before you commit. Most-recent first.
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CISO-grade rubric for AI agent governance with four concerns and six runtime capabilities.
Last calculated: May 2026
Custom pricing with dedicated tenant isolation, role-based access control, audit logs, and a dedicated account representative.
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