Platform MCP Server

ProAgentStore Platform

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/ FAGS Playwright browser runtime bundled into the CLI
├── workers/api/      Hono API worker (auth, agents, instances, 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/           5 flagship agents (site-monitor, lead-qualifier, etc.)
└── templates/        Agent scaffolding (worker, cron, api)

Agent types

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:

• https://proagentstore.online/docs/mcp/
• docs/mcp.md
• server.json
• .mcp.json
• AGENTS.md

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.

FAGS browser runtime

Browser-capable agents use PAGS as the control-plane brain and FAGS as the browser runtime/tool executor. Users install one public package, @proagentstore/cli; the FAGS Playwright runtime is bundled into it.

PAGS control plane / MCP
  -> task, auth, approval, audit
FAGS browser runtime
  -> Playwright, local files, browser profile
Real browser
  -> job boards, uploads, receipts

npm install -g @proagentstore/cli
pags runner start --port 49171 --token "$PAGS_RUNNER_TOKEN" --instance-id "$PAGS_INSTANCE_ID"
pags runner status --token "$PAGS_RUNNER_TOKEN" --instance-id "$PAGS_INSTANCE_ID"
pags runner task --type echo --input '{"ok":true}' --token "$PAGS_RUNNER_TOKEN" --instance-id "$PAGS_INSTANCE_ID"

Current local runtime mode uses a registered HTTPS endpoint. runner connect starts the FAGS runtime with a token and instance binding, opens a Cloudflare quick tunnel, and registers only the tunnel URL plus token with PAGS. Runtime registration is instance-scoped: PAGS stores the endpoint and encrypted runner token, then MCP/API proxy task calls to the runtime with X-PAGS-Instance-Id.

pags runner connect "$PAGS_INSTANCE_ID" --pags-token "$PAGS_TOKEN" --headless

runner connect is the current shipped local mode. It is the cheapest usable path today, but the target cheapest best-practice mode is outbound polling from the FAGS runtime to PAGS so the user's machine does not need a public tunnel. Manual setup is still available when you want to use a stable named tunnel:

pags runner register "$PAGS_INSTANCE_ID" \
  --endpoint-url "$PAGS_RUNNER_ENDPOINT" \
  --runner-token "$PAGS_RUNNER_TOKEN" \
  --pags-token "$PAGS_TOKEN" \
  --probe
pags runner runtime "$PAGS_INSTANCE_ID" --pags-token "$PAGS_TOKEN" --probe
pags runner run "$PAGS_INSTANCE_ID" --type echo --input '{"ok":true}' --pags-token "$PAGS_TOKEN"

The rentable job application agent uses the job.apply_basic runner task for basic resume-upload forms. The task is approval-gated and runs on the user's FAGS browser runtime:

pags runner run "$PAGS_INSTANCE_ID" \
  --type job.apply_basic \
  --input '{"url":"https://example.com/jobs/123","resumePath":"/path/to/resume.pdf","candidate":{"fullName":"Test Candidate","email":"candidate@example.com"},"coverNote":"I am interested in this role."}' \
  --pags-token "$PAGS_TOKEN"
pags runner approve-task "$PAGS_INSTANCE_ID" "$TASK_ID" --pags-token "$PAGS_TOKEN"

subscribe_agent -> register_instance_runtime -> instance_runtime_status(probe: true) -> run_instance_task -> approve_instance_task -> instance_task_events

The browser runtime MCP tools are register_instance_runtime, instance_runtime_status, unregister_instance_runtime, run_instance_task, approve_instance_task, cancel_instance_task, and instance_task_events.

The Console also shows FAGS runtime work as a kanban-style runtime board: open Console -> My Instances -> <instance> -> Runtime to see queued, running, approval-gated, blocked, completed, and cancelled tasks plus recent runtime events.

Skills and plugins

ProAgentStore publishes skills through platform-specific plugin marketplaces so users can find them from both Codex and Claude Code.

Codex:

codex plugin marketplace add ProAgentStore/platform

Claude Code:

/plugin marketplace add ProAgentStore/platform
/plugin install proagentstore@proagentstore
/reload-plugins

See Skill Publishing for the publishing layout, marketplace files, and dual Codex/Claude release checklist.

Public discovery pages:

• https://proagentstore.online/skills/
• https://proagentstore.online/skills/proagentstore-mcp-operator/
• https://proagentstore.online/llms.txt
• https://proagentstore.online/llms-full.txt
• https://proagentstore.online/skills.json

Flagship agents

Part of the FreeStore ecosystem

License

MIT