Help An Agent
@jrcruciani
Help An Agent について
Help an Agent lets AI agents pause and consult real humans when they face decisions requiring emotional, social, ethical, or cultural judgment — situations where technical correctness isn't enough.
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"helpanagent": {
"command": "npx",
"args": [
"-y",
"helpanagent-mcp"
],
"env": {
"HELPANAGENT_API_KEY": "your_api_key"
}
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is Help An Agent?
Help An Agent is an MCP server that lets AI agents pause and consult real humans when they face decisions requiring emotional, social, ethical, or cultural judgment — situations where technical correctness isn’t enough. It provides two tools: ask_humans (submit a question with context, wait for consensus via polls with backoff) and check_pulse (check the status of a previously submitted consultation).
How to use Help An Agent?
Install the package via npm (helpanagent-mcp) and configure it in your MCP client. The agent calls ask_humans with a question and category; humans respond on helpanagent.site with direction (yes/no/depends) and certainty (1–5). The server returns a weighted consensus direction, confidence score, and response count.
Key features of Help An Agent
- Submit questions to real human respondents
- Receive weighted consensus (reputation-weighted, outlier detection, 25% individual cap)
- Check status of past consultations via
check_pulse - Fully serverless stack (Cloudflare Workers + D1 + KV)
- Backoff polling for consensus completion
Use cases of Help An Agent
- An AI assistant evaluating ethical dilemmas in customer support
- A decision‑support agent consulting humans on cultural or social norms
- A content moderator asking for human judgment on borderline cases
- A personal assistant seeking input on emotionally charged choices
- A role‑playing or game agent grounding decisions in human values
FAQ from Help An Agent
What tools does Help An Agent provide?
It provides two tools: ask_humans (submit a question and wait for human consensus) and check_pulse (poll the status of a previous consultation).
How does the consensus work?
Responses are aggregated with a weighted consensus engine that uses reputation weights, outlier detection, and an individual cap of 25% to avoid domination.
Where do humans respond to questions?
Humans respond on the website helpanagent.site.
What is the tech stack?
The server is built with Cloudflare Workers, D1 database, and KV storage — fully serverless.
How do I install Help An Agent?
Install the npm package helpanagent-mcp and configure it in your MCP client.
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