原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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MCP Plesk Dev Docs

作者:barateza版本 0.6.0i★ –i在你的电脑上运行
注册名称io.github.barateza/mcp-plesk-dev-docs

安装

概览

作者提供的说明(英文原文)

An MCP server that indexes and retrieves Plesk documentation.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "plesk-dev-docs": {
      "command": "uvx",
      "args": [
        "mcp-plesk-dev-docs"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add plesk-dev-docs -- uvx mcp-plesk-dev-docs

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "plesk-dev-docs": {
      "command": "uvx",
      "args": [
        "mcp-plesk-dev-docs"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "plesk-dev-docs": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-plesk-dev-docs"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 barateza 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32489 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32489 个服务器的 10% 更新
  • 基础检查结果等于或优于此分类中其他 32489 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

MCP Plesk Dev Docs 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.6.0)于5个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Whisper

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211昨天更新
安装

Whisper

作者:whisper-sec

One routable IPv6 per AI agent, verifiable from the DNS root. Keyless tools need no signup.

电脑或云端今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

mcp-plesk-dev-docs

[!NOTE]

This MCP server provides unified documentation search for extension developers. If you are looking to manage your live Plesk server via AI, please see the official Plesk MCP Server.

State-of-the-Art (SOTA) semantic search across the entire Plesk documentation surface, optimized for sub-second latency on Apple Silicon.


Why this exists

Plesk documentation is spread across five separate sources: an admin guide, a REST API reference, a CLI reference, a PHP SDK, and a JS SDK. Answering a single extension development question often means searching all of them manually, cross-referencing results, and still missing the relevant section.

This server ingests all five sources, embeds them with a multilingual model, and exposes a single search_plesk_unified MCP tool. It uses hybrid search (Vector + FTS), Reciprocal Rank Fusion (RRF), and Cross-Encoder reranking to deliver high-precision results in milliseconds.


Architecture & Performance

flowchart TD

Client["MCP Client\n(Claude Desktop / Cursor / etc.)"]

Client -->|"search_plesk_unified(query)"| Server

subgraph Server["FastMCP Server · Modular Architecture"] direction TB Main["Bootstrap · server/main.py"] Life["Lifecycle Hooks · server/lifecycle.py"] Tools["MCP Tools · server/mcp_app.py"]

Main --> Life --> Tools end

subgraph Pipeline["Retrieval Pipeline"] direction TB E["1 · Embed query\n(Hardware-accelerated)"] S["2 · Hybrid Search\nVector (LanceDB) + FTS (Tantivy)"] R["3 · RRF Merge + Rerank\n(MiniLM-L4-v2)"] N["4 · Neighbor Expansion\n(Context Enrichment)"] A["5 · AI Synthesis\n(sampling-enabled)"] E --> S --> R --> N --> A end

subgraph Store["LanceDB Vector & FTS Store"] direction LR G["Guide"] A_["API"] C["CLI"] P["PHP Stubs"] J["JS SDK"] end

Tools --> Pipeline S <--> Store

Performance Benchmarks (2026-05-04)

Optimized for Apple Silicon (M2/M3) using MPS acceleration and memory-resident table caching.

ProfileEmbed ModelHR@5MRR@5Avg LatencyEst. RAM
`light`BAAI/bge-small100.0%0.9171.007 s~200 MB
`medium`BAAI/bge-base100.0%0.917~0.60s~600 MB
`full-tq`BAAI/bge-m375.0%0.750~0.40s~1300 MB

*Metrics measured on Apple M2 Pro with LanceDB connection caching enabled.*


Key Features

  • Single-Instance Lock: PID-based lock prevents concurrent LanceDB access when multiple MCP clients or IDE sessions try to launch the server simultaneously.
  • Sub-Second Hybrid Search: Combined Vector + Tantivy FTS with RAM-cached table connections for instant retrieval.
  • AST-Aware Chunking: Uses tree-sitter to respect class and method boundaries in PHP, JS, and TS documentation.
  • TurboQuant Acceleration: Fast 4-bit quantized search for the full-tq profile, delivering 10x lower latency for large models.
  • Neighborhood Retrieval: Automatically fetches adjacent chunks (prev/next) to provide complete context for grounding.
  • Macro-Context Summaries: Injects file-level purpose summaries into every chunk using the SummaryCache.
  • AI-Synthesized Answers: Generates concise answers from search results with structured inline citations [1], [2].

MCP Components

This server provides tools, prompts, and resources. See [docs/mcp-components.md](docs/mcp-components.md) for a full reference.

Primary Tools
ToolDescription
search_plesk_unifiedHybrid search with RRF and Cross-Encoder reranking.
get_file_contentRetrieve the full content of a specific documentation file.
resolve_referencesFind all files referencing a specific symbol or topic.
refresh_knowledgeRe-fetch sources and update the index (incremental).
trigger_index_syncStart a background indexing job.
daemon_healthCheck readiness, hardware acceleration (MPS/CUDA), and latency stats.
Resources
  • plesk://toc/api - Table of Contents for API documentation.
  • plesk://toc/cli - Table of Contents for CLI reference.
  • plesk://toc/guide - Table of Contents for Extensions Guide.
  • plesk://toc/php-stubs - Hierarchical list of PHP classes.

🚀 Installation & Setup

Because this server is published to PyPI and listed on the MCP Registry, you don't even need to clone the repository to run it!

Option 1: Run instantly via uvx (Recommended)

You can run or integrate the server in seconds.

1. Add to Claude Desktop

Add the server config to your claude_desktop_config.json (typically at ~/Library/Application Support/Claude/claude_desktop_config.json on macOS, or %APPDATA%\Claude\claude_desktop_config.json on Windows):

{

"mcpServers": { "plesk-dev-docs": { "command": "uvx", "args": ["mcp-plesk-dev-docs"] } } }

2. Configure in Cursor

Go to Settings > Features > MCP, click + Add New MCP Server:

  • Name: plesk-dev-docs
  • Type: command
  • Command: uvx mcp-plesk-dev-docs

Option 2: Local Developer Setup (Manual Build)

If you want to modify the source code, run benchmarks, or manage database migrations:

Quick bootstrap (recommended):

git clone https://github.com/barateza/mcp-plesk-dev-docs.git

cd mcp-plesk-dev-docs ./install.sh # Linux / macOS

powershell -ExecutionPolicy Bypass -File install.ps1 # Windows

Manual setup:

git clone https://github.com/barateza/mcp-plesk-dev-docs.git

cd mcp-plesk-dev-docs uv pip install -e ".[dev]"

  1. Run Initial Indexing: Generate the offline vector database and full-text search indexes:
   uv run python -m mcp_plesk_dev_docs.server.main refresh_knowledge
  1. Start the Server:
   uv run python -m mcp_plesk_dev_docs.server.main

Configuration

Set environment variables in .env:

PLESK_MODEL_PROFILE=light       # light | medium | full-tq

PLESK_ENABLE_SAMPLING=true # AI-Synthesized answers PLESK_DAEMON_AUTO_WARMUP=true # Preload models on startup PLESK_INDEX_SUMMARIES=true # Enable file-level summaries OPENROUTER_API_KEY=sk-or-v1-...


Documentation

  • [docs/benchmarks.md](docs/benchmarks.md) - Detailed latency and quality reports.
  • [docs/mcp-components.md](docs/mcp-components.md) - Full tool and resource reference.
  • [docs/turboquant.md](docs/turboquant.md) - 4-bit quantization internals.

License

MIT. See LICENSE.

Ownership & Disclaimer

This is a personal project by Gilson Siqueira. It is not officially affiliated with, endorsed by, or supported by Plesk or WebPros International GmbH. Plesk is a trademark of WebPros International GmbH.

Important notice about Plesk-owned deliverables

Portions of this repository were developed under contract for Plesk International GmbH ("Plesk") only if specifically identified as such. The MIT license above applies only to material the repository owner is authorized to license. Files or directories owned by Plesk, if any, are listed in NOTICE. If you need assurance about licensing for a particular file, contact Plesk or seek legal counsel before relying on the MIT License for Plesk-owned files.


*Built to make Plesk extension development faster.*

问 PopNx