Scalekit - 2026 Pricing, Features, Reviews & Alternatives

Scalekit is the agent integrations and tool calling platform for AI agents. It works as an MCP gateway between an agent and the tools it calls, managing authentication, permissions, execution, and logging, so engineering teams don't build or maintain that layer themselves.

The catalog covers 500+ pre-built connectors and 10,000+ tools across SaaS apps, APIs, and MCP servers, including Salesforce, Slack, Gmail, HubSpot, Zendesk, Gong, Notion, Snowflake, and Google Drive. Tool schemas are written for LLM tool calling rather than converted from API documentation, which improves how reliably agents select and call them. Teams can add custom tools on existing connectors in about 30 minutes, register their own connectors, or expose their tool stack over MCP.

Agents act as the specific user who delegated the task, not as a shared service account. Each tool call carries that user's identity, so downstream systems record the correct author, approval workflows continue to work, and enterprise security reviews have a clear delegation chain to evaluate.

Credentials are stored in an AES-256 encrypted vault, isolated per tenant, and never enter application code. OAuth flows and token refresh run automatically, and a Bring Your Own Key option is available for enterprise deployments. Permissions are checked per tool call, per connector, per tenant: a request outside what the user approved is blocked before it reaches the API.

Virtual MCP servers let teams define the exact tool set each agent, role, or user can access, composed from any combination of connectors and served over per-user authenticated URLs. Limiting the tool surface this way reduces token costs by up to 80%.

For monitoring, Scalekit provides per-connector health, error classification, tool call events, and log streaming to Datadog or Splunk. Every log records who authorized the call, which agent ran it, which tool it used, and what was returned.

Scalekit supports both deployment patterns for agents. Customer-facing agents connect to each customer's own tools using that customer's credentials, scopes, and tenant, with multi-tenant OAuth included. Internal agents act as the employee who triggered them, inheriting that person's SSO identity and permissions.

Framework adapters are available for LangChain, Google ADK, Anthropic, OpenAI, Vercel AI, Mastra, Claude Managed Agents, and OpenClaw, so existing tool schemas work without modification.

Von, an AI revenue intelligence platform, runs Scalekit in production: its agents work across Salesforce, Gong, Google Drive, and 140+ connectors on behalf of every customer, without rebuilding credential handling as tools were added. "Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work." (Venu Madhav Kattagoni, Head of Engineering, Von) Teams at MoEngage, Rocketlane, RocketBench, Westlink, Napkin.ai, and SiftHub also build on Scalekit.

The same platform also covers identity for SaaS products, in two forms. Auth for SaaS is a complete end-to-end auth stack: login, session management, RBAC, and user management, organized around organizations. Modular enterprise auth adds SSO (SAML and OIDC) and SCIM provisioning to an existing auth setup without replacing it. Either way, teams shipping a user-facing product alongside agent features manage user identity and agent access in one system instead of two vendors.

Scalekit runs as a cloud service with US or EU data residency, in a private cloud VPC, or self-hosted with air-gapped support. It is SOC 2 Type II and ISO 27001 certified, GDPR and HIPAA-ready, with 99.99% uptime and sub-50ms p95 tool execution.