Plori

ai.plori由 plori.ai 发布官方发布者v0.27.2更新于 Nov 8, 2026

Plori runs AI agents in cloud Workspaces.

已验证Streamable HTTP可网页运行云端与基础设施开发者工具AI 与机器学习

概览

AI 生成的概览

Plori 是远程 MCP 服务器,让助手在云端 Workspace 中运行 AI 代理,可创建工作区、发起运行并合并代理改动。

可以做什么
  • 管理工作区与账户:列出、创建、删除工作区,读取与上传工作区文件,查询运行费用与积分余额
  • 运行代理:向工作区会话发送消息并等待回复,获取运行结果、运行历史,取消运行,预约稍后运行
  • 处理人工介入:列出因审批或提问而暂停的运行,回答或拒绝输入请求
  • 协调工作代理:在各自的工作区文件副本上启动代理,列出与查看状态,向运行中的代理发送消息,停止任务组
  • 审阅变更集:提交、列出、查看、接受或拒绝工作代理的变更集,使改动成为新的工作区版本
适用场景
适合希望把编码、调研或内容工作交给各自在副本上作业、再由 Plori 合并结果的云端代理,并从自己的 MCP 客户端而非 Plori 网页应用驱动这些代理的场景。
运行要求
远程 streamable HTTP 端点,无需本地安装。首次连接需在浏览器中通过 OAuth 2.1 登录;无头或 CI 环境可使用在 Plori 仪表板生成的 API 密钥。需要已注册的 Plori 账户。仅支持 stdio 的客户端需使用 plori-mcp npm 包装包或 mcp-remote。
安装前请注意
运行代理会消耗账户中的预付积分,读取操作免费。工具可创建并永久删除工作区及其文件、版本和会话,可覆盖文件,接受变更集会替换工作区文件。MCP 客户端无法批准操作,每个暂停的审批都需在 Plori 网页应用中打开;预约运行也需在那里确认后才会排队。API 密钥可访问账户,应妥善保管并可随时撤销。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Plori,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/ai.plori%2Fplori/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "mcpServers": {
    "plori": {
      "type": "http",
      "url": "https://api.plori.ai/mcp"
    }
  }
}

README

plori

Plori runs AI agents that collaborate on one product in the cloud.

Plori runs AI agents that collaborate on one product in the cloud. Code, research, content: each works on its own copy, and Plori merges their changes back. The agents work in a cloud Workspace that keeps the product's files with saved revisions. Only the Workspace files persist between runs. 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

Paste this into your Claude Code conversation:

Set up https://plori.ai/SKILL.md

Claude reads the setup instructions and configures MCP if needed. If the new server has not loaded, type /reload-plugins when Claude asks, then continue in the same conversation. With pairing, open the short address Claude shows, enter the code, sign in, and approve. You can use a phone while Claude Code runs on a remote machine. No installed skill or plugin is required.

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

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

Codex CLI

sh
codex mcp add plori --url https://api.plori.ai/mcpcodex 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):

sh
npx plori-mcp# headless / CI: authenticate with an API key instead of the OAuth flownpx 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.

Or skip MCP: your own terminal

The plori CLI is not an MCP client. It is a door of its own, and it opens the same live session the web app shows: the recent history, a prompt, streaming output, and the approval queue in one place. A turn you send in the terminal appears in an open browser tab as it streams.

sh
curl -fsSL https://plori.ai/install.sh | shplori login && plori attach <agent-name>

The installer drops one static binary in ~/.local/bin and needs no Node; if that directory is not on your PATH yet, the script prints the line to add. npm i -g @plori/cli works too. The argument to attach is an agent name, an agent id, or a session id, so a session id copied out of the web app works on its own. Ctrl-D detaches and leaves the run going on the server.

The terminal does not give the agent access to your local files. The shell and the Workspace files are in Plori's cloud.

Verify the connection

Ask your client:

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

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

What the tools do

The server exposes 24 tools in five groups. A Workspace holds durable files with saved revisions, a main conversation, and run history. An agent runs in a Workspace with a shell and the Workspace files under /workspace.

  • Workspaces and account: list_workspaces (the Workspaces you own, with state, default agent, current revision, and storage_readiness while storage starts), create_workspace (a Workspace with its first revision. Unless you pass default_manager_agent_id, it also creates a default agent. idempotency_key makes a retry return the same Workspace), delete_workspace (permanently delete a Workspace with its files, revisions, copies, and conversations), read_workspace_file (a file or a directory listing in a saved revision), upload_workspace_file (write a file into a Workspace's current files, replacing any file at path; pass UTF-8 text as content, or omit content for a one-time upload_url for a larger or binary file), get_workspace_costs (the amount charged for the runs of a Workspace or of one task group in a time window), get_credits (prepaid balance, plan, and limits).
  • Runs: send_workspace_message (send a message to a Workspace conversation and wait for the reply, with wait_seconds to set how long to hold, idempotency_key to make a retry return the original run, and callback_url plus callback_secret to post a signed status notification to your endpoint), get_run_result (a run's status, timestamps, credits, tokens, tool progress, and the reply once it finishes; for a Workspace manager that waits for its workers, worker_inputs lists the workers' open questions and approvals and next_run_id names the run that continues it), list_runs (an agent's run history, most recent first), cancel_run (stop an in-flight run, which reports cancelling and then cancelled), schedule_run (run an agent once later, after a delay or at a timestamp. It returns awaiting_confirmation and a confirm_url. Plori queues the run only after you confirm it in the Plori web app).
  • Human-in-the-loop: list_pending_inputs (runs paused on an approval or an input request), answer_pending_input (deny one, or answer an agent's question, which starts a continuation run). An MCP client cannot approve an action: each paused approval carries an approve_url that you open in the Plori web app.
  • Workers: create_workspace_worker (start an agent on its own copy of the Workspace files, so several workers run at the same time without changing each other's files), list_workspace_workers and get_workspace_worker (status, run, and whether Plori saved the worker's files), steer_workspace_worker (send a message into a running worker's turn), stop_workspace_task_group (stop every worker of a task group).
  • Changesets: when a worker's run completes normally and changes at least one file, Plori submits its saved files and accepts a clean comparison itself. submit_workspace_changeset (submit the saved files of a worker whose run ended in error, was cancelled or was stopped, for comparison with the Workspace's current files), list_workspace_changesets and get_workspace_changeset (state, phase, and changed and conflicting paths), accept_workspace_changeset (the worker's changes become the Workspace's current files as a new revision), reject_workspace_changeset (keep the Workspace files as they are).

A turn that is still running when the hold ends continues on the server: send_workspace_message returns a run_id with status running and a poll_after_seconds delay, and you read the answer with get_run_result using wait=true (or your own wait_seconds, up to 1800).

Costs: 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

来源:README.md,提交 287eeff

工具

0
该服务器需要登录,因此 SourceWeft 无法在没有账号的情况下读取其工具,也未收录。已连接账号所能看到的内容可能因账号及其权限而异。

版本历史

20
  1. v0.27.1Nov 6, 2026
  2. v0.27.0Nov 3, 2026
  3. v0.26.2Oct 31, 2026
  4. v0.26.1Oct 29, 2026
  5. v0.26.0Oct 26, 2026
  6. v0.25.0Oct 22, 2026
  7. v0.24.0Oct 18, 2026
  8. v0.23.0Oct 14, 2026
  9. v0.22.0Oct 13, 2026
  10. v0.20.1Oct 12, 2026
  11. v0.20.0Oct 10, 2026
  12. v0.18.0Oct 5, 2026
  13. v0.17.0Oct 1, 2026
  14. v0.16.4Sep 28, 2026
  15. v0.16.3Sep 26, 2026
  16. v0.16.2Sep 21, 2026
  17. v0.16.1Sep 20, 2026
  18. v0.16.0Sep 19, 2026
  19. v0.15.0Sep 18, 2026
  20. v0.14.2Sep 16, 2026

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