Question 1

Is Arcade compatible with existing AI development frameworks?

Accepted Answer

Yes. Arcade is framework agnostic. Build with LangChain, LlamaIndex, Mastra, CrewAI, Pydantic, Google ADK, or OpenAI Agents. The same flexibility extends across the stack: any agent client, including Claude, Cursor, ChatGPT, Copilot, or your own, and any LLM. Connect the Arcade runtime to your existing Python or JavaScript codebase and your agents start taking authorized actions right away.

Question 2

What tools can AI agents access using Arcade?

Accepted Answer

AI agents using Arcade access a catalog of pre-built Model Context Protocol tools for major systems like Google Workspace, Slack, Microsoft, and Salesforce. Developers can also build custom tools using the open-source Arcade framework in Python or JavaScript, or bring existing MCP tools into Arcade. The Arcade Registry lets you share and discover all your MCP tools.

Question 3

Can I add custom policies to Arcade for AI agents?

Accepted Answer

Yes. Arcade supports pre- and post-tool-call hooks that let your team add custom policies without forking the runtime. Inspect every request before it runs and every response before it returns. Block sensitive actions, redact PII, and stop data from leaving systems it shouldn't. The runtime enforces your policies on every call.

Question 4

Can I deploy Arcade on my own infrastructure?

Accepted Answer

Yes. You can deploy the Arcade MCP runtime in your own cloud environment, a virtual private cloud, on-premises, or in a fully air-gapped environment. This deployment flexibility gives enterprise teams control over where data lives and how it is secured.

Question 5

How does Arcade secure AI agent actions?

Accepted Answer

Arcade enforces user-specific permissions through your existing OAuth and identity provider flows. Agents act only on behalf of the authenticated user, not through broad service accounts. The runtime gives you visibility and control over every tool your AI agent accesses.

Question 6

What is an MCP runtime for AI agents?

Accepted Answer

An MCP runtime is the infrastructure layer that enables AI agents to securely connect to external tools and business systems. Arcade is the MCP runtime that handles user authentication, authorization, policy enforcement, and tool execution. Developers deploy production-ready AI agents without building custom integration infrastructure.

Question 7

How does Arcade govern AI agent actions?

Accepted Answer

Arcade enforces permissions through your existing OAuth and identity provider flows. Agents act on behalf of the authenticated user, never through broad service accounts. Every action runs at the intersection of what the user can do and what the agent is scoped to do. Cross either line and the action stops. You see and control every tool your agent touches.

ArcadeCouche d'action pour les agents IA afin d'exécuter des tâches réelles dans les applications et les API

Aperçu

Fonctionnalités clés

Tarifs

Cas d’usage

Construire des copilotes IA avec des actions réelles

Alimenter les flux de travail d'agents autonomes

Définir des outils personnalisés pour les LLM

Ajouter de l'automatisation aux produits existants

Pour & contre

Pour

Contre

Avis

Years in this space

Does the job

Skeptical, then convinced

Use it every day

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