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Aiprox Workflows

通过 AIProx 的 MCP 工具创建、运行、查询和删除多智能体工作流,把搜索、情感分析、抓取、翻译、视觉识别、代码审计等能力串联成流水线,支持定时调度与邮件或 webhook 投递结果,按闪电网络 sats 计费,并提供预置模板与异步回调。

unixlamadev-spec
unixlamadev-spec
热度 70.80
最近更新 2026-06-03 00:31:15
分类:自动化依赖:MCP 服务 / 第三方 API应用场景:工作流 / 日程安排 / 研究 / 报告撰写 ...

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add aiprox-workflows
Metadata
name
aiprox-workflows
description
Create and run multi-agent AI workflows on AIProx. Chain agents into scheduled pipelines. Pay per execution in sats.
acceptLicenseTerms
true
metadata
{"clawdbot":{"emoji":"⚡","homepage":"https://aiprox.dev/workflows","requires":{"env":["AIPROX_SPEND_TOKEN"]}}}

AIProx Workflows

AIProx Workflows is a multi-agent pipeline engine. Chain AI agents into named workflows, schedule them to run on a cron, and get results delivered by email or webhook. Pay per execution in sats — no subscriptions, no monthly fees.

When to Use

  • Building automated pipelines that chain multiple AI agents
  • Scheduling recurring tasks (daily news digest, competitive intel, market signals)
  • Running one-off multi-step pipelines on demand
  • Any workflow where one agent's output feeds into the next

MCP Tools

create_workflow

Create a named pipeline with ordered agent steps.

Create a workflow "daily-crypto-brief" that searches Bitcoin news, analyzes sentiment, and emails a summary @daily

Step chaining: use $step1.result, $step2.result, etc. to pass outputs forward.

Available capabilities:

Capability What it does
web-search Real-time web search via search-bot
sentiment-analysis Sentiment and tone analysis via sentiment-bot
scraping Web scraping and article extraction via data-spider
data-analysis Data processing and text analysis via doc-miner
translation Multilingual translation via polyglot
vision Image/screenshot analysis via vision-bot
code-execution Code audit and security review via code-auditor
email Send email notifications via email-bot
market-data Prediction market signals via market-oracle
token-analysis Solana token safety and rug detection via isitarug

run_workflow

Trigger any workflow by its ID.

Run workflow wf_abc123

list_workflows

Show all workflows for the current spend token.

List my workflows

get_run_history

Show past execution results, sats spent, and step-by-step output.

Show run history for wf_abc123

delete_workflow

Delete a workflow (cancels scheduled runs).

run_template

Run a pre-built template by name in one shot.

Run the polymarket-signals template and email me at user@example.com

Pre-Built Templates

Template name Pipeline Cost
news-digest search-bot → sentiment-bot → email-bot ~150 sats/run
token-scanner data-spider → isitarug → email-bot ~120 sats/run
competitive-intel search-bot → doc-miner → sentiment-bot → email-bot ~200 sats/run
multilingual-content data-spider → doc-miner → polyglot ~180 sats/run
site-audit vision-bot → code-auditor → doc-miner ~220 sats/run
polymarket-signals market-oracle → sentiment-bot → email-bot ~160 sats/run
api-security-audit data-spider → code-auditor → pdf-bot → email-bot ~300 sats/run

Authentication

Set AIPROX_SPEND_TOKEN in your MCP server config. Get a spend token at lightningprox.com.

{
  "mcpServers": {
    "aiprox-workflows": {
      "command": "npx",
      "args": ["aiprox-workflows-mcp"],
      "env": {
        "AIPROX_SPEND_TOKEN": "lnpx_your_token_here"
      }
    }
  }
}

Scheduling

Shorthand When
@hourly Every hour
@daily Every day at midnight
@weekly Every Sunday
0 9 * * 1-5 9am Monday–Friday

Pricing

50–220 sats per workflow execution depending on agents used. No monthly plan. Deducted from your Lightning spend token balance.

Behavior Guidelines

When a user asks to automate something:

  1. Identify which capabilities are needed (search → analyze → notify is the common pattern)
  2. Suggest a template if one matches, otherwise offer to create a custom workflow
  3. Confirm the schedule and email/webhook if they want recurring runs
  4. After creating, offer to run it immediately

Cost transparency:

  • Mention estimated sats cost before creating/running
  • Report sats_spent after each run

Check templates first: If the task matches a template, use run_template — it's faster and pre-configured.

Async Execution

For one-off orchestrate requests (not scheduled workflows), add callback_url to get a job_id back immediately and receive the result via webhook when done. Poll status at GET https://aiprox.dev/api/async/:job_id. Works with Zapier, Make, and n8n.

Links