confirm-mcp
Provides a human-approval tool for MCP-compatible agents, pausing execution until a human approves or edits the action, with every decision logged.
README
confirm-mcp
An MCP server that gives any MCP-compatible agent (Claude Desktop, Cursor, and others) a human-approval tool. Before the agent does something irreversible, it calls request_approval, a human approves or edits the action at confirm.dev, and the agent proceeds with the approved result. Every decision is logged.
Setup
Get an API key at confirm.dev, then add the server to your MCP client config.
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"confirm": {
"command": "npx",
"args": ["-y", "confirm-mcp"],
"env": { "CONFIRM_API_KEY": "cfm_live_..." }
}
}
}
That's it. The agent now has two tools.
Tools
request_approval
Pause and ask a human to approve a sensitive action. Blocks until the human decides or the wait elapses.
| Input | Description |
|---|---|
summary |
One line the human reads, e.g. "Refund $10,000 to customer #4821". Required. |
notify |
Approver email, or group:<key> to escalate to an approver group. Required. |
payload |
The exact action as structured data. The human can edit it before approving. |
reasoning |
Why the agent wants to do this. |
recent_actions |
The agent's recent steps, for context (max 10). |
ttl_minutes |
How long the request stays valid (5 to 10080). |
wait_minutes |
How long to block before returning "pending" (default 15). |
On APPROVED, the tool returns the effectivePayload to use (the human may have edited it). On REJECTED or EXPIRED, it tells the agent to stop. If the wait elapses while still pending, it returns the request id so the agent can poll later.
check_approval
Poll a previously created request by id to see whether a human has decided.
Why a tool, not a prompt
The approval is enforced server-side: the agent cannot fake a verdict, and every decision is recorded in an immutable audit log. Teaching the agent when to call this (via a system prompt or an agent skill) is the coverage layer; the tool is the enforcement layer.
For production agents where you need guaranteed coverage of specific actions, use the deterministic policy engine in @confirm/sdk (guard()) rather than relying on the model to remember to call the tool.
Docs: confirm.dev/docs. Node 18+.
Development
This package is developed in a private monorepo alongside the Confirm.dev service and mirrored here on every release, which is why the history starts at the first public release. Issues and PRs are welcome; PRs get cherry-picked upstream.
Build: npm install && npm run build. Test: node smoke.mjs (after a build; uses a mocked client, no network).
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.