Platform

Name: Platform
Author: LLM Mart

No install snippet on purpose. A working MCP config is a command, its arguments and an environment block — the last two are where API keys live, so this catalogue never stores them and cannot publish them. Follow the link above for the authors' own instructions.

Marketplace for server-powered AI agents. Creators build agent templates, clients subscribe and run them on their own data.

Store: https://proagentstore.online API: https://api.proagentstore.online MCP: https://mcp.proagentstore.online/mcp Console: https://proagentstore.online/console/ GitHub: https://github.com/ProAgentStore Free pair: https://freeagentstore.online

What's in here

platform/
├── packages/sdk/     Internal TypeScript SDK for agents
├── packages/cli/     @proagentstore/cli — init, check, publish, MCP proxy, local runtime
├── packages/browser-runner/ ProAgentStore Playwright + terminal/coding runtime bundled into the CLI
├── workers/api/      Hono API worker (auth, agents, instances, coding, apply, keys, analytics)
├── workers/host/     Marketing site + console + widget
├── workers/mcp/      MCP server for Codex, Claude Code, Cursor, and VS Code
├── store/            Source HTML for all pages
├── skills/           Open Agent Skills source files
├── plugins/          Codex and Claude plugin wrappers
├── agents/           Tier-0 first-party agent sources kept in this repo
└── templates/        Agent scaffolding (worker, cron, api)

Agent types

Type	Template	What it does
Agent	`worker`	Full AI: conversation, memory, knowledge base, core tools, Workers AI
Worker	`cron`	Scheduled tasks: daily digests, monitoring, batch processing
Tool	`api`	Stateless endpoint: transform, generate, analyze

Quick start

Use an agent

# Try any published agent — no sign-up needed
curl -X POST https://api.proagentstore.online/v1/public/agents/chatbot/try \
  -H "Content-Type: application/json" \
  -d '{"message":"Hello!"}'

Build an agent

npx @proagentstore/cli init my-agent --template worker
cd my-agent
pnpm install && pnpm dev
npx @proagentstore/cli publish

SDK

import { initPro } from '@proagentstore/sdk'

const agent = initPro({ agentId: 'your-id', token: 'your-token' })
const { response } = await agent.chat('Hello!')

Embed widget

<script src="https://proagentstore.online/widget.js"
  data-agent="chatbot" data-theme="dark"></script>

MCP

codex mcp add proagentstore --url https://mcp.proagentstore.online/mcp
codex mcp list
# If the server shows "Not logged in":
codex mcp login proagentstore

claude mcp add --transport http proagentstore https://mcp.proagentstore.online/mcp
claude mcp list

npx mcp-remote https://mcp.proagentstore.online/mcp
npx @proagentstore/cli mcp

MCP has two runtime modes:

chat_with_agent calls the public trial endpoint. Use it for discovery and smoke tests.
subscribe_agent creates your private instance, then chat_with_instance runs that instance with your own state, knowledge, and caller-provided AI credentials.

Typical user run:

list_agents -> subscribe_agent -> my_instances -> add_instance_knowledge -> chat_with_instance

The expected response when user-owned AI credentials are missing is:

Add your Cloudflare Workers AI account ID and API token before running this agent.

That means the instance runtime path is working and correctly refusing to bill the platform AI account. See MCP Instance Runtime for the full tool map, live test record, and OAuth troubleshooting.

The full MCP-first developer surface is documented at:

MCP safety is enforced server-side. OAuth supports read, write, runtime, and destructive scopes; MCP_READ_ONLY=1 forces read-only mode; mutating tools support dry_run where useful; overwrite/destructive tools require exact confirm values; and mcp_audit_log exposes recent MCP write, runtime, dry-run, denied, and destructive events.