Scalekit
Let your agents act as users with secure OAuth flows, token vault, and scoped permissions across 8000+ apps. One SDK handles authentication and tool calling.
Editor's Verdict
Key Takeaways
- Delegated OAuth & Token Management
- Built-in Token Vault
- Scoped Authorization
- 8000+ Pre-built Tools & Connectors
In-Depth Review: What is Scalekit?
Scalekit provides a unified authentication and authorization layer for AI agents, enabling them to act on behalf of users with delegated OAuth, token storage, and scoped permissions. It handles token refresh, credential vaulting (AES-256), and tool call observability, so your agent and model never see sensitive credentials. With 500+ pre-built connectors and support for custom APIs, Scalekit integrates with frameworks like LangChain, OpenAI, and Anthropic. Deploy agents securely across your team with built-in token vault, per-tool permissions, and full audit logs.
Core Features
Delegated OAuth & Token Management
Scalekit handles OAuth flows, token refresh, and credential storage so agents can act on behalf of users without exposing credentials to the agent or model.
Built-in Token Vault
AES-256 encrypted vault stores tokens per tenant; agents receive opaque references, keeping sensitive data out of logs and memory.
Scoped Authorization
Permissions are scoped per tool call, not per agent, ensuring agents cannot act beyond what the current tool call is authorized for.
8000+ Pre-built Tools & Connectors
Access 500+ pre-built connectors (Gmail, Slack, Salesforce, etc.) with 8000+ callable actions; custom connectors also supported.
Agent Logs & Observability
Full attribution on every log: who authorized, which agent, which tool, and the response. Exportable to SIEM with 90-day retention.
Multi-region & High Availability
US and EU regions with automatic failover, 99.99% uptime SLA, and data residency enforcement.
Private Cloud & On-premise Deployments
Deploy in your VPC or on-premises for full data boundary control; HIPAA-ready on request.
Framework Agnostic Integrations
Native integrations with LangChain, Google ADK, Anthropic, OpenAI, Vercel AI, Mastra, and more; Node.js and Python SDKs.
Pricing
Free
- 5,000 tool calls per month (hard stop)
- Unlimited connected accounts
- 500+ pre-built connectors
- Bring your own credentials
- Community + email support
- 30-day audit log retention
Growth
- 200,000 tool calls per month (overage $0.25 per 1K)
- Unlimited connected accounts
- 500+ pre-built connectors
- Custom connectors & API proxy
- Customization & branding included
- Private Slack support
- EU data residency
- 30-day audit log retention
Enterprise
- Custom tool call volume and rates
- Unlimited connected accounts
- VPC / on-prem deployment
- 99.99% uptime SLA
- Forward deployed engineer + CSM
- SIEM integrations
- Custom audit log retention (up to 1 year)
Pros and Cons
Pros
- Enhanced SecurityCredentials never enter agent context or models; stored in AES-256 encrypted vault with per-tenant isolation.
- Fine-grained AuthorizationPermissions scoped per tool call prevents agents from exceeding authorized actions.
- Extensive Integration Library500+ pre-built connectors and 8000+ actions, plus ability to build custom connectors for any API.
- Full ObservabilityComplete audit trail with attribution; exportable to SIEM for compliance and debugging.
- Easy Setup and Framework SupportInstall via CLI, drop-in SDK, works with major AI frameworks; from install to first tool call in minutes.
Cons
- Limited Free TierFree plan caps at 5,000 tool calls per month with hard stop, which may be insufficient for production use.
- Overage CostsGrowth plan charges $0.25 per 1K extra tool calls, which can add up for high-volume deployments.
- Dependency on Third-party ServiceAgent authentication and tool-calling rely on Scalekit's infrastructure; potential latency or downtime if not self-hosted.
- Learning Curve for Custom ConnectorsBuilding custom connectors requires defining auth patterns and tool schemas, which may require developer effort.
- Limited Framework Support for Some AgentsWhile supporting major frameworks, niche or older frameworks may lack native integration.
Use Cases & Recommended Professions
AI Agent Developer→ View Toolkit
Needs to quickly connect agents to multiple SaaS tools with secure, delegated authentication without managing OAuth flows.
Product Engineer→ View Toolkit
Building agentic features for users; requires seamless integration with third-party APIs and scoped permissions.
Security Engineer→ View Toolkit
Responsible for ensuring credentials are never exposed to agents or models; needs encryption, audit logs, and compliance.
CTO / Technical Lead→ View Toolkit
Oversees agent deployment at scale; needs reliable, observable infrastructure with enterprise-grade security and SLAs.
DevOps / Platform Engineer→ View Toolkit
Manages internal agent gateway and MCP servers; requires control plane for connector catalog, identity routing, and logging.
Integration Specialist→ View Toolkit
Connects agents to internal APIs or custom tools; needs ability to build custom connectors and manage credential injection.
Frequently Asked Questions
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ℹ️ Curation Disclosure: The overview and features of Scalekit were synthesized using AI and fact-checked by our curation team to ensure accuracy.