review-gate-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@review-gate-mcpExtract invoice fields from this document and hold uncertain ones for review"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
review-gate-mcp
An MCP server that asks a human when it isn't sure.
Most extraction demos guess. This one implements the pattern that makes automation safe to run on documents that matter: fields extracted with high confidence flow through; anything uncertain is held in a review queue for a person to resolve - never silently guessed into your systems.
document ──▶ extract_with_gate ──▶ confident fields ──▶ your system
│
└──▶ uncertain fields ──▶ review_queue ──▶ a human ──▶ resolve_reviewTools
tool | what it does |
| extract |
| list items waiting for a human decision |
| a human supplies the verified value, closing the loop |
Related MCP server: Investment Memorandum Processor MCP Server
Run it
npm install
npm test # end-to-end over real MCP stdio: extract -> hold -> human resolveAdd to Claude Code / Claude Desktop / Cursor (any MCP client):
{
"mcpServers": {
"review-gate": { "command": "node", "args": ["/path/to/review-gate-mcp/server.js"] }
}
}Then ask your agent to extract fields from a pasted document and watch what it does with the smudged one.
The point
The extractors here are deliberately transparent heuristics - swap in a model-backed extractor and the gate stays identical. The pattern is the product: a system that escalates its hard cases beats one that guesses them. This is the standard RavnLab builds automation to; the evaluation side of the same idea lives in ravnlab-eval-harness.
MIT. Built by RavnLab.
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