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Gumloop provides native MCP support with 50+ pre-built servers for popular services like GitHub, Slack, Notion, and HubSpot, plus the ability to connect custom HTTPS-accessible MCP servers. OpenAI and Anthropic models execute MCP tools natively, while other providers like Gemini and Groq use Gumloop's backend connector approach. This enables standardized integration with existing business systems while maintaining enterprise security.
Gumstack provides organization-wide AI usage tracking across all systems, not just Gumloop workflows. It monitors tool calls from Claude Code, ChatGPT, Cursor, and internal AI systems through a centralized logging layer. Combined with SOC 2 Type II certification, RBAC, VPC deployments, and comprehensive audit trails, it gives security teams complete visibility and control over enterprise AI adoption.
Credits are consumed based on operation complexity: basic actions use 1-5 credits while advanced AI model calls (GPT-4.1, Claude) consume 10-20+ credits per operation. Web scraping, batch processing, and parallel executions also consume credits. The Pro plan includes 20,000+ monthly credits, and users can bring their own API keys to reduce AI-related credit usage for cost optimization.
Yes, Gumloop provides comprehensive REST API with JavaScript and Python SDKs enabling programmatic workflow triggering, agent management, and file operations. Workflows can be exposed as webhook endpoints, integrated into existing business systems, and called from external applications. Agents can also be deployed directly in Slack, Teams, and email for natural language interaction.
Gumloop maintains zero data retention agreements with third-party AI model providers, ensuring customer data isn't used for model training. The platform is SOC 2 Type II certified and GDPR compliant, offering features like custom data retention rules, comprehensive data exports, incognito mode for sensitive operations, and configurable AI model access controls for compliance with industry regulations.
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