Model Context Protocol (MCP) Server: ai.thrain/askhuman

The ai.thrain/askhuman MCP server provides an ask_human tool that lets agents escalate decisions to real people and receive judgments back. The server’s purpose is to connect agent decision-making with human evaluation when automated outputs require review.

🛠️ Key Features

Offers an ask_human tool
Escalates agent decisions to real people
Returns human judgments to the agent

🚀 Use Cases

Human-in-the-loop decision escalation for agent workflows
When an agent needs a human judgment to proceed

⚡ Developer Benefits

Integrates human review into agent-driven processes via a single tool

⚠️ Limitations

Human judgment is required for the escalated decisions, implying a dependency on real people

AskHuman

The control layer that makes AI agents deployable. Agents call ask_human when they hit a consequential business action (purchase orders, refunds, price changes — anything that moves money, inventory, or customers); the question is delivered to real humans (Slack, Discord, webhook, or a web inbox); the answer flows back to the blocked agent with a human signature, rationale, and full audit trail.

Positioning (decided 2026-07-26): we gate agent-initiated business actions — ops, not code review. Dev workflows (PRs) already have native approval rails; business operations don't. Chartroom dogfooding exercises the mechanics; the market is ops.

Live: https://askhuman.thrain.ai · A thrain.ai product. MIT licensed, free to use.

MCP server: npx -y @thrain/askhuman-mcp (see packages/mcp).

Phase roadmap

Phase 0 (this repo, live): escalation-as-a-service — customers' own humans answer. SaaS, no marketplace. Validates the interface.
Phase 1: concierge marketplace — route to our human pool (hand-recruited).
Phase 2: open supply — worker app, calibration traps, reputation, consensus votes.
Phase 3: agent fleets — SLA capacity contracts + compliance audit trails.

Architecture

code

agent ──MCP `ask_human` / POST /v1/asks──▶ Cloudflare Worker (Hono) ── D1
                                              │
                        Slack / Discord / webhook / web inbox
                                              │
                              human taps tokenized answer link
                                              │
agent ◀── long-poll GET /v1/asks/:id/wait ────┘

worker/ — the whole service: API, answer pages, inbox, landing page. Cloudflare Worker + D1, deployed at askhuman.thrain.ai.
packages/mcp/ — stdio MCP server exposing ask_human + ask_human_status. Private (not published to npm yet — licence/scope pending, same as Blackout).
docs/API.md — the HTTP API contract.

Develop & deploy (this box)

bash

source <(grep '^export CLOUDFLARE_' ~/.bashrc)
export npm_config_cache=/mnt/ext4dev/npm-cache
cd worker
npm install
npm run deploy               # wrangler deploy
npm run db:schema:remote     # apply schema.sql to prod D1

Secrets: ADMIN_SECRET (wrangler secret; also exported as ASKHUMAN_ADMIN_SECRET in ~/.bashrc on the box). Provision accounts:

bash

curl -s -X POST https://askhuman.thrain.ai/admin/accounts \
  -H "x-admin-secret: $ASKHUMAN_ADMIN_SECRET" \
  -H "content-type: application/json" \
  -d '{"name":"Acme","email":"ops@acme.com"}'
# → returns api_key (once!) and inbox_url

Use the MCP server (any MCP client)

bash

export ASKHUMAN_API_KEY=ah_live_...
claude mcp add askhuman -e ASKHUMAN_API_KEY=$ASKHUMAN_API_KEY \
  -- node /mnt/ext4dev/repos/askhuman/packages/mcp/src/index.js

The agent gets an ask_human(question, type, options?, sla_seconds?, max_wait_seconds?) tool that blocks until a human answers (or returns still-pending with resume instructions).

ai.thrain/askhuman

Model Context Protocol (MCP) Server: ai.thrain/askhuman

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

AskHuman

Phase roadmap

Architecture

Develop & deploy (this box)

Use the MCP server (any MCP client)

Install

Configuration