Create and drive plori agents (each an AI agent on its own cloud computer) from any MCP client, the plori CLI, or over REST. Covers authentication (OAuth 2.1 or API key), creating agents, invoking them and reading replies, answering human-in-the-loop requests, and scheduling deferred runs.
Scanned 9/12/2026
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---
name: plori
description: "Create and drive plori agents (each an AI agent on its own cloud computer) from any MCP client, the plori CLI, or over REST. Covers authentication (OAuth 2.1 or API key), creating agents, invoking them and reading replies, answering human-in-the-loop requests, and scheduling deferred runs."
category: ai-agents-and-harness
source_repo: hashgraph-online/awesome-codex-plugins
source_path: "plugins/plori-ai/codex-plugin/skills/plori/SKILL.md"
source_url: https://github.com/hashgraph-online/awesome-codex-plugins/blob/HEAD/plugins/plori-ai/codex-plugin/skills/plori/SKILL.md
---
# Using plori from an agent
plori (https://plori.ai) gives you AI agents. Each agent runs on its own cloud computer with a
persistent disk, a shell, developer tools, and memory. You can create agents, send them
work, and read their replies programmatically.
## Connect
MCP (recommended for a hosted client): Streamable HTTP at `https://api.plori.ai/mcp`.
- OAuth 2.1: compliant MCP clients connect with no hand-copied key. An unauthenticated
request returns 401 with the discovery chain (RFC 9728 Protected Resource Metadata at
https://api.plori.ai/.well-known/oauth-protected-resource, then dynamic client
registration and authorization code + PKCE). The account owner signs in once with an
email one-time code.
- API key: the account owner provisions a key at https://plori.ai and you send
`Authorization: Bearer plori_sk_...`.
CLI (recommended from a terminal): `npm i -g @plori/cli`, or run it without installing
via `npx -y @plori/cli`, gives you the `plori` command for the same operations from your
shell. Authenticate with `plori login` or by setting `PLORI_API_KEY`. Output is
human-readable on a terminal and a single JSON document when piped or with `--json`, so it
composes in scripts. Commands are listed under "CLI commands" below.
REST: the same operations at `https://api.plori.ai/v1` with the same bearer token.
Full authentication instructions: https://plori.ai/auth.md
## Tools
Account and agents: `list_agents`, `get_agent`, `create_agent`
(name, optional model), `set_agent_model`, `delete_agent`, `get_credits`,
`get_usage`, `get_disk`.
Runs: `invoke_agent` sends a message and by default blocks until the turn finishes,
returning the assistant's reply. Pass `wait=false` to get a `run_id` immediately and
poll `get_run_result`. `list_runs` lists recent runs.
Human in the loop: a run can pause on an approval or input request (status
`awaiting_input`). Read the queue with `list_pending_inputs` and reply with
`answer_pending_input` (run_id + tool_call_id, then approved=true/false for approvals
or value for input requests).
Deferred work: `schedule_run` (agent_id, prompt, and delay_seconds or an RFC3339
fire_at) invokes the agent later as an ordinary run.
Workflows: `list_workflows`, `create_workflow` (name, optional description/trigger_kind/
cron_expr), `run_workflow` (runs a workflow now: a real execution billed like any run,
returning the execution, terminal or still `running`), and `get_workflow_execution` to poll
one. A workflow's steps are built by an agent; these tools manage and run the result.
## CLI commands
The CLI mirrors the tools above; an agent is addressable by name or id, and every command
accepts `--json`.
- `plori create <name>`: get or create an agent by name (reusing a name returns the
existing agent). `plori agents`, `plori agent <name>`, `plori set-model <name> <model>`,
`plori delete <name> --yes`.
- `plori run <name> "message"`: send a message and, by default, wait for the reply and
print it. Add `--follow` to stream the turn live, or `--no-wait` to get a run id back
immediately. Pass `-` as the message to read it from stdin.
- `plori result <name> <run-id>` (add `--wait` to block) and `plori runs <name>` read
run status and history.
- `plori inputs <name>` lists runs paused on a human request; `plori answer <run-id>
<tool-call-id> --approve|--deny|--value <v>` replies.
- `plori schedule <name> "prompt" --in <seconds>` (or `--at <rfc3339>`) defers a run;
`plori schedules <name>` and `plori unschedule <name> <id>` manage them.
- `plori workflows list`, `plori workflows create <name> [--trigger cron --cron <expr>]`,
`plori workflows run <name|id>` (run it now), `plori workflows execution <name|id> <exec-id>`.
- `plori credits`, `plori usage`, `plori disk` read account state.
## Costs and limits
Running an agent spends credits; check `get_credits` before invoking. Agent count and
model tier follow the account's plan. Every call is scoped to the account that owns the
credential; there is no cross-account access.
## More
- Integration front door: https://plori.ai/agents.md
- MCP connect guide: https://plori.ai/mcp
- CLI on npm: https://www.npmjs.com/package/@plori/cli
- Authentication detail: https://plori.ai/auth.md
- Site map for agents: https://plori.ai/llms.txt
---
**Source:** [`hashgraph-online/awesome-codex-plugins`](https://github.com/hashgraph-online/awesome-codex-plugins) → `plugins/plori-ai/codex-plugin/skills/plori/SKILL.md`
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