plori

official

Create and drive plori cloud agents (each an AI agent on its own cloud computer)

GitHub

What can you do with Plori MCP?

  • List your agents — Ask the AI to call list_agents so you can see every agent on your account and their current status.
  • Create a new agent — Have the AI provision a persistent cloud agent with create_agent, specifying a name and model.
  • Run an agent and get its reply — Trigger an agent with run_agent and read back its response, either blocking or fire-and-forget.
  • Check your credit balance — Use get_credits to see how many plori credits remain before running paid operations.
  • Answer pending agent questions — Retrieve an agent’s human-in-the-loop questions and supply answers so it can continue.
  • Schedule a deferred run — Ask the AI to schedule an agent run for later, letting work happen while you’re away.

Documentation

plori

Give your AI agent its own cloud computer.

plori hosts agents: each one gets a persistent machine with a real disk, real tools, and memory that survives between conversations. Idle agents scale to zero. You talk to your agents in the web app, or drive them from your own tools over MCP and REST.

This repository is the integration front door. The product itself lives at plori.ai; the remote MCP server lives at https://api.plori.ai/mcp.

Connect your MCP client

plori is a remote MCP server (streamable HTTP). There is nothing to install or run locally. Sign-in happens in your browser via OAuth 2.1 the first time your client connects; headless environments can use an API key instead.

Claude Code

claude mcp add --transport http plori https://api.plori.ai/mcp

Cursor

Use the one-click Add to Cursor button, or add manually: Settings -> MCP -> Add server with URL https://api.plori.ai/mcp.

VS Code

code --add-mcp '{"name":"plori","type":"http","url":"https://api.plori.ai/mcp"}'

Codex CLI

codex mcp add plori --url https://api.plori.ai/mcp
codex mcp login plori

Codex auto-detects plori's OAuth on login. One-install alternative with the skill bundled: codex plugin marketplace add plori-ai/codex-plugin then codex plugin add plori@plori.

Cline

Follow llms-install.md, written for Cline's automated installer.

Any other client

Native streamable-HTTP clients connect to https://api.plori.ai/mcp directly. Clients that only speak stdio can bridge with the plori-mcp npm package (a thin wrapper around mcp-remote with the endpoint pinned; this repository is its source):

npx plori-mcp
# headless / CI: authenticate with an API key instead of the OAuth flow
npx plori-mcp --header "Authorization: Bearer plori_sk_..."
# equivalent, without the wrapper:
npx mcp-remote https://api.plori.ai/mcp

API keys are minted in Dashboard -> Settings on a registered account.

Verify the connection

Ask your client:

List my plori agents and tell me how many credits I have left.

You should see list_agents and get_credits tool calls and a real answer.

What the tools do

The server exposes 15 tools in four groups:

  • Agents: list, inspect, create, and delete agents; pick the model an agent runs.
  • Runs: invoke an agent and read its reply (blocking or fire-and-forget), list runs, fetch a past result.
  • Human-in-the-loop: list an agent's pending questions and answer them.
  • Scheduling: schedule a deferred run so an agent works while you are away.

Costs: creating and running agents spends plori credits from your account. Reading (lists, results, balances) is free. The pricing page has the details; revoke a client's access any time in your client's settings, or revoke the API key in Dashboard -> Settings.

For AI agents reading this

The machine-readable entry points:

  • Front door: plori.ai/agents.md
  • Site index: plori.ai/llms.txt
  • Skill: SKILL.md (index: /.well-known/agent-skills/index.json)
  • MCP server card: https://api.plori.ai/mcp/server-card
  • OAuth discovery: RFC 9728 protected-resource metadata on api.plori.ai, dynamic client registration supported
  • Registry entry: ai.plori/plori in the official MCP Registry

Every page on plori.ai is also served as Markdown: append .md to the path or send Accept: text/markdown.

Docs and support