Best AI Agent Infrastructure Tools

An MCP-compatible actions runtime that lets AI agents securely authenticate users, call business tools, and enforce governance outside the model.

Key Features:

• •Chrome extension screen capture for instant demo recording
• •Hotspots, guided tooltips, and callout annotations
• •Embeddable demos with customizable player appearance

Arcade.dev is an actions runtime that gives AI agents permission-aware tools, delegated user authorization, policy enforcement, and auditable execution.

Key Features:

• •MCP runtime designed for secure production AI agent deployments
• •Connects to identity providers, enforces agent authorization, and enables actions in Google, Slack, Salesforce, and other tools
• •OAuth handling, permission challenges, hosted MCP servers, audit logs, RBAC, SSO, and SAML on higher tiers

E2B Desktop is a hosted computer environment for AI agents that helps teams run GUI and desktop-style automation inside isolated cloud sandboxes.

Key Features:

• •Isolated cloud sandboxes for agent execution
• •Desktop-style environments for GUI automation
• •Hosted computers that agents can control

Convex Agent Component is a Convex component for building persistent agent applications that helps teams combine application data, conversation state, and tool-driven AI behavior in a backend.

Key Features:

• •Persistent conversation and agent state
• •Agent threads connected to application data
• •Backend integration inside a Convex application

Cloudflare Agents SDK is a framework for stateful AI agents on Cloudflare that helps teams build and deploy agents that maintain state and use tools.

Key Features:

• •Stateful agents built on Cloudflare's globally distributed runtime
• •Durable workflow patterns for agents that must survive across requests
• •Tool calling for connecting models to application actions

A hosted runtime for composing tools, agents, models, memory, objectives, and embeddable agent experiences.

Key Features:

• •Hosted agent loops
• •Model and behavior variations
• •Unified tool layer

MintMCP is an enterprise MCP gateway and AI-agent governance platform for controlling tool access, identity, security monitoring, and audit trails.

Key Features:

• •Central gateway for approved MCP servers and models
• •Role-based bundles with tool-level controls
• •Per-agent identities with delegated and revocable credentials

Klavis AI provides live, verifiable environments and training data for teams developing coding and tool-using AI agents.

Key Features:

• •Live training environments spanning more than 600 real tools and SaaS applications
• •Production MCP servers for realistic agent tool use
• •Long-horizon, state-mutating workflows with logically consistent state and noisy inputs