AgentSidekick
A safety layer that reviews every action your AI agent is about to take, flags risky or wrong tool choices, and asks for your approval in plain language before anything runs.
small business owners running AI agents (Claude Desktop, Make, n8n) to automate customer support, CRM, or scheduling tasks
- Pre-execution action review with plain-language explanations of what the agent wants to do
- Confidence score and 'did the agent pick the right tool for this?' flag
- One-click rules to block or require approval for specific actions (e.g. 'never delete rows')
- Weekly digest summarizing every agent decision and what you overrode
A front-page HN post just showed that official MCP servers from Notion, MongoDB, Airtable, and GitHub score D/F on agent usability — meaning non-technical teams adopting these agents today are getting silently wrong actions in production.
HN post with 23 points reflects developer awareness, but small-business end users aren't yet aware their AI agents are silently misfiringAgentic AI Safety Playbook 2025 | Guardrails, Permissions & Governance ... ↗
Existing MCP lint tools target server developers, not the non-technical operator who needs to trust the agentAgentic AI Safety Playbook 2025 | Guardrails, Permissions & Governance ... ↗
B2B SaaS pricing per seat for teams running AI agents is a tested willingness-to-pay patternAgentic AI Safety Playbook 2025 | Guardrails, Permissions & Governance ... ↗
Agent safety remains critical as MCP-based agents proliferate into every SaaS category
Wrapping MCP tool calls with a review/approval layer is straightforward middleware to build