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openserv-client

Complete guide to using @openserv-labs/client for managing agents, workflows, triggers, and tasks on the OpenServ Platform. Covers provisioning, authentication, x402 payments, ERC-8004 on-chain identity, and the full Platform API.

Install / Use

npx skills add internet-court/internet-court-skill --skill openserv-client

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

96/100

Category

Automation

Supported Platforms

Universal

Our assessment of openserv-client

openserv-client scores 96/100 on our quality scale, 182nd of 1,985 Automation skills we index (top 10%).

Its SKILL.md is 17 KB long, well organised into 31 sections with 20 code examples: a thorough specification that gives an agent plenty to work with.

With 6,129 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
16/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 39 days ago, so openserv-client is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

openserv-client compared with similar skills

All 4 of these similar skills score higher than openserv-client; compare them before choosing.

SkillScoreStarsUpdatedFormat
openserv-client (this skill)by internet-court966.1k39d agoSKILL.md
Agent-Reachby Panniantong10085.9k12d agoCLAUDE.md
headroomby headroomlabs-ai10074.0k1d agoCLAUDE.md
rufloby ruvnet10073.4ktodayCLAUDE.md
crawl4aiby unclecode10084.4k3d agoMCP Server

Frequently asked questions

How do I install openserv-client?
Run npx skills add internet-court/internet-court-skill --skill openserv-client. The install tabs above show the steps for each supported agent.
Which AI agents does openserv-client work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is openserv-client safe to use?
It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is openserv-client still maintained?
The repository was last updated 39 days ago, so openserv-client is actively maintained.

name: openserv-client description: Complete guide to using @openserv-labs/client for managing agents, workflows, triggers, and tasks on the OpenServ Platform. Covers provisioning, authentication, x402 payments, ERC-8004 on-chain identity, and the full Platform API. IMPORTANT - Always read the companion skill openserv-agent-sdk alongside this skill, as both packages are required to build any agent. Read reference.md for the full API reference.

OpenServ Client

The @openserv-labs/client package is the TypeScript client for the OpenServ Platform API. You use it whenever your code needs to talk to the platform—to register an agent, create workflows, set up triggers, or run tasks.

Why you need this package

Your agent (built with @openserv-labs/sdk) runs on your machine or server. The platform doesn’t know about it until you tell it: what the agent is, where it’s reachable, and how it can be triggered. The client is how you do that. It lets you create a platform account (or reuse one), register your agent, define workflows and triggers (webhook, cron, manual, or x402 paid), and bind credentials so your agent can accept tasks. Without it, your agent would have no way to get onto the platform or receive work.

What you can do with it

  • Provision — One-shot setup: create or reuse an account (via wallet), register the agent, create a workflow with trigger and task, and get API key and auth token. Typically you call provision() once per app startup; it’s idempotent.
  • Platform API — Full control via PlatformClient: create and list agents, workflows, triggers, and tasks; fire triggers; run workflows; manage credentials. Use this when you need more than the default provision flow.
  • Model Parameters — Configure which LLM model and parameters the platform uses for your agent's tasks. Set model_parameters on agent creation/update or via provision().
  • Models API — Discover available LLM models and their parameter schemas via client.models.list().
  • x402 payments — Expose your agent behind a paywall; callers pay per request (e.g. USDC) before the task runs. Provision can set up an x402 trigger and return a paywall URL.
  • ERC-8004 on-chain identity — Register your agent on-chain (Base), mint an identity NFT, and publish service metadata to IPFS so others can discover and pay your agent in a standard way.

Reference: reference.md (full API) · troubleshooting.md (common issues) · examples/ (runnable code)

Installation

npm install @openserv-labs/client

Quick Start: Just provision() + run()

The simplest deployment is just two calls: provision() and run(). That's it.

You need an account on the platform to register agents and workflows. The easiest way is to let provision() create one for you: it creates a wallet and signs you up with it (no email required). That account is reused on every run.

See examples/agent.ts for a complete runnable example.

Key Point: provision() is idempotent. Call it every time your app starts - no need to check isProvisioned() first.

What provision() Does

  1. Creates or reuses an Ethereum wallet (and platform account if new)
  2. Authenticates with the OpenServ platform
  3. Creates or updates the agent (idempotent)
  4. Generates API key and auth token
  5. Binds credentials to agent instance (if agent.instance is provided)
  6. Creates or updates the workflow with trigger and task
  7. Creates workflow graph (edges linking trigger to task)
  8. Activates trigger and sets workflow to running
  9. Persists state to .openserv.json

Workflow Name & Goal

The workflow config requires two important properties:

  • name (string) - This becomes the agent name in ERC-8004. Make it polished, punchy, and memorable — this is the public-facing brand name users see. Think product launch, not variable name. Examples: 'Viral Content Engine', 'Crypto Alpha Scanner', 'Life Catalyst Pro'.
  • goal (string, required) - A detailed description of what the workflow accomplishes. Must be descriptive and thorough — short or vague goals will cause API calls to fail. Write at least a full sentence explaining the workflow's purpose.
workflow: {
  name: 'Deep Research Pro',
  goal: 'Research any topic in depth, synthesize findings from multiple sources, and produce a comprehensive report with citations',
  trigger: triggers.webhook({ waitForCompletion: true, timeout: 600 }),
  task: { description: 'Research the given topic' }
}

Agent Instance Binding (v1.1+)

Pass your agent instance to provision() for automatic credential binding:

const agent = new Agent({ systemPrompt: '...' })

await provision({
  agent: {
    instance: agent, // Calls agent.setCredentials() automatically
    name: 'my-agent',
    description: '...',
    model_parameters: { model: 'gpt-5', verbosity: 'medium', reasoning_effort: 'high' } // Optional
  },
  workflow: { ... }
})

// agent now has apiKey and authToken set - ready for run()
await run(agent)

This eliminates the need to manually set OPENSERV_API_KEY environment variables.

Model Parameters

The optional model_parameters field controls which LLM model and parameters the platform uses when executing tasks for your agent (including runless capabilities and generate() calls). If not provided, the platform default is used.

await provision({
  agent: {
    instance: agent,
    name: 'my-agent',
    description: '...',
    model_parameters: {
      model: 'gpt-4o',
      temperature: 0.5,
      parallel_tool_calls: false
    }
  },
  workflow: { ... }
})

Discover available models and their parameters:

const { models, default: defaultModel } = await client.models.list()
// models: [{ model: 'gpt-5', provider: 'openai', parameters: { ... } }, ...]
// default: 'gpt-5-mini'

Provision Result

interface ProvisionResult {
  agentId: number
  apiKey: string
  authToken?: string
  workflowId: number
  triggerId: string
  triggerToken: string
  paywallUrl?: string // For x402 triggers
  apiEndpoint?: string // For webhook triggers
}

API Keys: Agent vs User

provision() creates two types of credentials. They are not interchangeable:

| Credential | Env Variable | Used By | Purpose | | ------------- | ----------------------- | ---------------- | --------------------------------------------------------------------------------------------------------------------------------------------- | | Agent API key | OPENSERV_API_KEY | SDK internals | Authenticates the agent when receiving tasks from the platform. Set automatically via agent.instance. Do not use with PlatformClient. | | Wallet key | WALLET_PRIVATE_KEY | PlatformClient | Authenticates your account for management calls (list tasks, debug workflows, manage agents). | | User API key | OPENSERV_USER_API_KEY | PlatformClient | Alternative to wallet auth. Get from the platform dashboard. |

If you get a 401 Unauthorized when using PlatformClient, you are likely using the agent API key by mistake. Use wallet authentication or the user API key instead.


PlatformClient: Full API Access

For advanced use cases, use PlatformClient directly:

import { PlatformClient } from '@openserv-labs/client'

// Using wallet authentication (recommended — uses wallet from provision)
const client = new PlatformClient()
await client.authenticate(process.env.WALLET_PRIVATE_KEY)

// Or using User API key (NOT the agent API key)
const client = new PlatformClient({
  apiKey: process.env.OPENSERV_USER_API_KEY // NOT OPENSERV_API_KEY
})

See reference.md for full API documentation on:

  • client.agents.* - Agent management
  • client.workflows.* - Workflow management
  • client.triggers.* - Trigger management
  • client.tasks.* - Task management
  • client.models.* - Available LLM models and parameters
  • client.integrations.* - Integration connections
  • client.payments.* - x402 payments
  • client.web3.* - Credits top-up

Triggers Factory

Use the triggers factory for type-safe trigger configuration:

import { triggers } from '@openserv-labs/client'

// Webhook (free, public endpoint)
triggers.webhook({
  input: { query: { type: 'string', description: 'Search query' } },
  waitForCompletion: true,
  timeout: 600
})

// x402 (paid API with paywall)
triggers.x402({
  name: 'AI Research Assistant',
  description: 'Get comprehensive research reports on any topic',
  price: '0.01',
  timeout: 600,
  input: {
    prompt: {
      type: 'string',
      title: 'Your Request',
      description: 'Describe what you would like the agent to do'
    }
  }
})

// Cron (scheduled)
triggers.cron({
  schedule: '0 9 * * *', // Daily at 9 AM
  timezone: 'America/New_York'
})

// Manual (platform UI only)
triggers.manual()

Timeout

Important: Always set timeout to at least 600 seconds (10 minutes) for webhook and x402 triggers. Agents often take significant time to process requests — especially in multi-agent workflows or when performing research, content generation, or other complex tasks. A low timeout (e.g., 180s) will cause premature failures. When in doubt, err on the side of a longer timeout. For multi-agent pipelines with many sequential steps, consider 900 seconds or more.

Input Schema

Define fields for webhook/x402 paywall UI:

triggers.x402({
  name: 'Content Writer',
  description: 'Generate polished content on any topic',
  price: '0.01',
  input: {
    topic: {
      type: 'string',
      title: 'Content Topic',
      description: 'Enter the subject you want covered'
    },
    style: {
      type: 'string',
      title: 'Writing Style',
      enum: ['formal', 'casual', 'humorous'],
      default: 'casual'
    }
  }
})

Cron Expressions

┌───────────── minute (0-59)
│ ┌───────────── hour (0-23)
│ │ ┌───────────── day of month (1-31)
│ │ │ ┌───────────── month (1-12)
│ │ │ │ ┌───────────── day of week (0-6, Sunday=0)
* * * * *

Common: 0 9 * * * (daily 9 AM), */5 * * * * (every 5 min), 0 9 * * 1-5 (weekdays 9 AM)


Deploy to OpenServ Cloud

Deploy your agent to the OpenServ managed cloud with:

npx @openserv-labs/client deploy [path]

Where [path] is the directory containing your agent code (defaults to current directory).

Prerequisites

  1. OPENSERV_USER_API_KEY in .env — Your .env file in the agent directory must contain OPENSERV_USER_API_KEY. Get this from the OpenServ platform dashboard. This key is required by the deploy command (and by PlatformClient for management operations). Note that provision() itself does not need this key — it creates its own wallet, authenticates, and persists credentials to .openserv.json independently. The user API key is also saved to .openserv.json after provision if present.

  2. Call provision() first — provision() must run at least once before deploying. It registers the agent on the platform and persists credentials to .openserv.json. The recommended agent template already calls provision() before run(agent) in main(), so starting the agent locally (npm run dev or npx tsx src/agent.ts) is enough. If your code does not call provision() (e.g., you only call run(agent) in a custom script), you must add an explicit provision() call and run it once before deploying.

Deploy Workflow

1. Set OPENSERV_USER_API_KEY in .env
2. Call provision() during local startup (npm run dev) — registers the agent and writes .openserv.json
3. npx @open

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars6.1k
CategoryAutomation
Updated1mo ago
Forks110

Languages

TypeScript

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium