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  1. Home
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  3. Plori
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Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 9:15:46 AM

Plori

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cloud-agentsdeveloper-toolsworkflowsmcp

Remote MCP access to persistent cloud agents, including runs, approvals, schedules, workflows, and account data.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "plori-ai-plori": {
      "command": "npx",
      "args": [
        "-y",
        "plori-mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿค– More in Coding Agents

Overview

The plori-ai/plori MCP server connects clients to hosted plori agents with persistent disks, command-line tools, and durable memory. It uses streamable HTTP at https://api.plori.ai/mcp, with OAuth 2.1 in interactive clients or an API key for headless use. Tools cover agent management, runs, human approvals, scheduling, workflows, and account reads. Reach for it when an agent needs a persistent cloud environment rather than access to the local machine.

Use cases

โ€ขCreate and manage persistent cloud agents
โ€ขRun deferred tasks while away
โ€ขAnswer agent approval questions
โ€ขExecute and monitor multi-step workflows
โ€ขInspect credits, usage, and connected providers

Key features

โ€ขRemote streamable HTTP MCP endpoint
โ€ขPersistent agent disks and memory
โ€ขAgent runs with cancellation and result retrieval
โ€ขHuman-in-the-loop approval queue
โ€ขDeferred runs and workflow execution
โ€ขCredit, usage, disk, and connection reads

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Plori.

Extracted Tool Capabilities
Remote streamable HTTP MCP endpoint
Persistent agent disks and memory
Agent runs with cancellation and result retrieval
Human-in-the-loop approval queue
Deferred runs and workflow execution
Credit, usage, disk, and connection reads

How Plori works

What plori-ai/plori MCP server does

The plori-ai/plori MCP server gives an MCP client access to hosted agents running in plori.ai. Each agent has its own persistent machine, disk, tools, and memory, so state can remain available between sessions. The server is intended for driving those agents from an AI client or another MCP-compatible application rather than operating files on the developer's computer.

Available operations span the agent lifecycle and its work. You can list, inspect, create, and delete agents; start runs and retrieve their replies; inspect or cancel active work; and handle questions that require human input. The service also supports deferred runs and multi-step workflows. Account tools expose credit balances, usage, disk information, and the configured third-party connections without returning tokens or client secrets.

How it works

The service is hosted and exposes a streamable HTTP MCP endpoint at https://api.plori.ai/mcp. There is no local MCP process to build or launch for clients that support this transport. Interactive clients authenticate through a browser using OAuth 2.1 on first connection. Headless environments can send a plori API key as a bearer token instead.

Runs can be blocking, allowing the client to wait for a result, or fire-and-forget. Workflow operations include reading definitions, editing drafts with compare-and-swap behavior, starting executions, and checking execution status and per-step data. Creating or running agents consumes credits, while list operations, result retrieval, and balance reads are free according to the supplied documentation.

Setup and configuration

For the plori-ai/plori MCP server, configure a remote HTTP MCP connection with the endpoint https://api.plori.ai/mcp. Cursor provides an add-server flow and Cline has a dedicated installation guide. Claude Code and VS Code examples are also provided in the project documentation, as is a Codex CLI setup that performs OAuth login.

A client that only supports stdio can use the separately published plori-mcp npm wrapper, which forwards requests to the same remote endpoint. That wrapper is not the MCP service itself. For CI or other noninteractive environments, pass an API key in the Authorization: Bearer ... header. Keys are created from Dashboard โ†’ Settings on a registered plori account.

Tools and capabilities

The documented tool groups include:

  • Agents: list, inspect, create, and delete agents.
  • Runs: invoke agents, read results, list runs, retrieve past results, and cancel in-flight work.
  • Human-in-the-loop: list pending agent questions and submit answers.
  • Scheduling: arrange a run for a later time.
  • Workflows: list, inspect, edit, create, execute, and monitor workflows, including version and step data.
  • Account reads: check credits, usage, disk details, and connected OAuth providers.

The agent platform's router selects a model for each task. Workflow execution is a real, billed operation, while account and historical read operations do not consume credits as described in the README.

Limitations and notes

This connection does not provide the cloud agent with access to the user's local files. Shell commands, files, and disk data belong to the agent's hosted environment. The service requires a registered account for API-key creation, and agent creation or execution can incur credit usage. OAuth access can be revoked in the MCP client's settings, while API keys can be revoked from the plori dashboard.

The repository is an integration front door for the hosted product; the remote MCP implementation is served by plori.ai rather than run from this repository. Clients must support streamable HTTP directly or use an appropriate bridge for stdio-only environments.

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

Last commit
4d ago
Most recent push to the default branch.
Directory activity
6 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Plori

You do not install a local server. Configure an MCP client to connect to https://api.plori.ai/mcp over streamable HTTP.

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Technical Specs & Signals

Category๐Ÿค–Coding Agents
PricingFreemium
More technical detailsExpand โ–พ
TransportSTDIO
RuntimeNode.js
AuthOAuth
ClientsCursor, Cline / VS Code
Last updatedSep 6, 2026
9/10 checks healthy over the last 32d
Views6
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit4d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 6, 2026
53Quality signal: Good ยท 53/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools25/30
Adoption & activity4/15
Community engagement1/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 15d ago via OSV.dev ยท plori-mcp (npm)

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