Skip to main content
Glama
dylangroos

Patchright Lite MCP Server

by dylangroos

Patchright Lite MCP Server

Ein optimierter Model Context Protocol (MCP)-Server, der das Patchright Node.js SDK umschließt, um KI-Modellen Stealth-Browser-Automatisierungsfunktionen zu bieten. Dieser schlanke Server konzentriert sich auf wesentliche Funktionen, um die Nutzung einfacherer KI-Modelle zu vereinfachen.

Was ist Patchright?

Patchright ist eine unerkannte Version des Test- und Automatisierungsframeworks Playwright. Es ist als direkter Ersatz für Playwright konzipiert, verfügt jedoch über erweiterte Tarnfunktionen, um die Erkennung durch Anti-Bot-Systeme zu verhindern. Patchright unterstützt verschiedene Erkennungstechniken, darunter:

  • Runtime.enable-Leck

  • Console.enable-Leck

  • Befehlskennzeichen-Lecks

  • Allgemeine Erkennungspunkte

  • Geschlossene Shadow Root-Interaktionen

Dieser MCP-Server umschließt die Node.js-Version von Patchright, um deren Funktionen KI-Modellen über ein einfaches, standardisiertes Protokoll zur Verfügung zu stellen.

Related MCP server: Puppeteer-Extra MCP Server

Merkmale

  • Einfache Benutzeroberfläche : Konzentriert sich auf die Kernfunktionalität mit nur 4 wesentlichen Tools

  • Stealth-Automatisierung : Verwendet den Stealth-Modus von Patchright, um eine Erkennung zu vermeiden

  • MCP-Standard : Implementiert das Model Context Protocol für eine einfache KI-Integration

  • Stdio Transport : Verwendet Standard-Eingabe/Ausgabe für nahtlose Integration

Voraussetzungen

  • Node.js 18+

  • npm oder yarn

Installation

  1. Klonen Sie dieses Repository:

    git clone https://github.com/yourusername/patchright-lite-mcp-server.git
    cd patchright-lite-mcp-server
  2. Installieren Sie Abhängigkeiten:

    npm install
  3. Erstellen Sie den TypeScript-Code:

    npm run build

Verwendung

Führen Sie den Server aus mit:

npm start

Dadurch wird der Server mit stdio-Transport gestartet und ist bereit für die Integration mit KI-Tools, die MCP unterstützen.

Integration mit KI-Modellen

Claude Desktop

Fügen Sie dies zu Ihrer Datei claude-desktop-config.json hinzu:

{
  "mcpServers": {
    "patchright": {
      "command": "node",
      "args": ["path/to/patchright-lite-mcp-server/dist/index.js"]
    }
  }
}

VS Code mit GitHub Copilot

Verwenden Sie die VS Code CLI, um den MCP-Server hinzuzufügen:

code --add-mcp '{"name":"patchright","command":"node","args":["path/to/patchright-lite-mcp-server/dist/index.js"]}'

Verfügbare Tools

Der Server bietet nur 4 wesentliche Tools:

1. Durchsuchen

Startet einen Browser, navigiert zu einer URL und extrahiert Inhalte.

Tool: browse
Parameters: {
  "url": "https://example.com",
  "headless": true,
  "waitFor": 1000
}

Widerrufsfolgen:

  • Seitentitel

  • Sichtbare Textvorschau

  • Browser-ID (für nachfolgende Vorgänge)

  • Seiten-ID (für nachfolgende Operationen)

  • Screenshot-Pfad

2. Interagieren

Führt eine einfache Interaktion auf einer Seite aus.

Tool: interact
Parameters: {
  "browserId": "browser-id-from-browse",
  "pageId": "page-id-from-browse",
  "action": "click", // can be "click", "fill", or "select"
  "selector": "#submit-button",
  "value": "Hello World" // only needed for fill and select
}

Widerrufsfolgen:

  • Aktionsergebnis

  • Aktuelle URL

  • Screenshot-Pfad

3. Auszug

Extrahiert bestimmten Inhalt von der aktuellen Seite.

Tool: extract
Parameters: {
  "browserId": "browser-id-from-browse",
  "pageId": "page-id-from-browse",
  "type": "text" // can be "text", "html", or "screenshot"
}

Widerrufsfolgen:

  • Extrahierter Inhalt basierend auf dem angeforderten Typ

4. Schließen

Schließt einen Browser, um Ressourcen freizugeben.

Tool: close
Parameters: {
  "browserId": "browser-id-from-browse"
}

Beispiel für einen Nutzungsablauf

  1. Starten Sie einen Browser und navigieren Sie zu einer Site:

    Tool: browse
    Parameters: {
      "url": "https://example.com/login",
      "headless": false
    }
  2. Füllen Sie ein Anmeldeformular aus:

    Tool: interact
    Parameters: {
      "browserId": "browser-id-from-step-1",
      "pageId": "page-id-from-step-1",
      "action": "fill",
      "selector": "#username",
      "value": "user@example.com"
    }
  3. Passwort eingeben:

    Tool: interact
    Parameters: {
      "browserId": "browser-id-from-step-1",
      "pageId": "page-id-from-step-1",
      "action": "fill",
      "selector": "#password",
      "value": "password123"
    }
  4. Klicken Sie auf die Schaltfläche „Anmelden“:

    Tool: interact
    Parameters: {
      "browserId": "browser-id-from-step-1",
      "pageId": "page-id-from-step-1",
      "action": "click",
      "selector": "#login-button"
    }
  5. Text extrahieren, um die Anmeldung zu bestätigen:

    Tool: extract
    Parameters: {
      "browserId": "browser-id-from-step-1",
      "pageId": "page-id-from-step-1",
      "type": "text"
    }
  6. Schließen Sie den Browser:

    Tool: close
    Parameters: {
      "browserId": "browser-id-from-step-1"
    }

Sicherheitsüberlegungen

  • Dieser Server bietet leistungsstarke Automatisierungsfunktionen. Verwenden Sie ihn verantwortungsbewusst und ethisch.

  • Vermeiden Sie die Automatisierung von Aktionen, die gegen die Nutzungsbedingungen von Websites verstoßen würden.

  • Beachten Sie die Ratenbegrenzungen und überlasten Sie Websites nicht mit Anfragen.

Lizenz

Dieses Projekt ist unter der MIT-Lizenz lizenziert – Einzelheiten finden Sie in der Datei LICENSE.

Danksagung

  • Patchright-nodejs von Kaliiiiiiiiii-Vinyzu

  • Modellkontextprotokoll von modelcontextprotocol

Docker-Nutzung

Sie können diesen Server mit Docker ausführen:

docker run -it --rm dylangroos/patchright-mcp

Lokales Erstellen des Docker-Images

Erstellen Sie das Docker-Image:

docker build -t patchright-mcp .

Führen Sie den Container aus:

docker run -it --rm patchright-mcp

Docker Hub

Das Image wird automatisch im Docker Hub veröffentlicht, wenn Änderungen in den Hauptzweig integriert werden. Das neueste Image finden Sie unter: dylangroos/patchright-mcp

Available Tools

4 tools
browseB

Browse to a URL and return the page title and visible text

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to navigate to
headlessNoWhether to run the browser in headless mode
waitForNoTime to wait after page load (milliseconds)

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return values (page title and visible text) but lacks critical details such as error handling (e.g., for invalid URLs), performance implications (e.g., timeouts), authentication needs, or rate limits, which are important for a browsing tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose and outcome with zero wasted words. It is appropriately sized for the tool's complexity and gets straight to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and return values but lacks details on behavioral traits and usage guidelines, leaving gaps that could hinder an AI agent's effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the schema already documents all parameters (url, headless, waitFor) thoroughly. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage nuances, but this is acceptable given the high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('browse to a URL') and the outcome ('return the page title and visible text'), using specific verbs and resources. It distinguishes itself from sibling tools like 'close', 'extract', and 'interact' by focusing on navigation and content retrieval rather than closing, extraction, or interaction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'extract' or 'interact', nor does it mention any prerequisites, exclusions, or specific contexts for usage. It states what the tool does but not when it's appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

closeC

Close browser to free resources

ParametersJSON Schema
NameRequiredDescriptionDefault
browserIdYesBrowser ID to close

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It states the tool closes a browser to free resources, implying a destructive action that terminates a session, but doesn't disclose behavioral traits like whether it's reversible, requires specific permissions, affects other tools, or has side effects (e.g., losing unsaved data). The mention of 'free resources' adds some context but is minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste, front-loading the key action and purpose. It's appropriately sized for a simple tool with one parameter.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and a destructive action implied by 'close', the description is incomplete. It lacks details on what happens after closing (e.g., return values, error conditions), prerequisites, or integration with sibling tools. For a tool that likely terminates a resource, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the parameter 'browserId' fully documented in the schema. The description adds no meaning beyond the schema, as it doesn't explain what a 'browserId' is, how to obtain it, or its format. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Close') and the resource ('browser'), specifying it's to 'free resources'. It distinguishes from sibling tools like 'browse' (open/access) and 'interact' (use while open), but doesn't explicitly contrast with 'extract' (which might operate on a closed or open browser).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when resources need freeing, but provides no explicit guidance on when to use this tool versus alternatives (e.g., whether to close after 'browse' or 'extract'), prerequisites, or exclusions. It lacks context for decision-making relative to siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

extractC

Extract information from the current page as text, html, or screenshot

ParametersJSON Schema
NameRequiredDescriptionDefault
browserIdYesBrowser ID from a previous browse operation
pageIdYesPage ID from a previous browse operation
typeYesType of content to extract

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but lacks behavioral details. It doesn't disclose whether extraction is read-only (implied but not stated), if it requires specific permissions, rate limits, or what happens on failure (e.g., invalid IDs). The description only states what it does, not how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It front-loads the core action ('extract information') and specifies key details (source: current page; formats: text, html, screenshot). Every element earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 3 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain the relationship to 'browse' (source of browserId/pageId), what 'extract' returns (e.g., raw text, file path), or error handling. The agent lacks context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are well-documented in the schema. The description adds minimal value by mentioning the 'type' enum options (text, html, screenshot), but doesn't explain semantics beyond what the schema already provides (e.g., what 'text' extraction includes vs. 'html'). Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'extract' and the resource 'information from the current page', specifying the output formats (text, html, or screenshot). It distinguishes from sibling tools like 'browse' (which likely navigates) and 'interact' (which likely performs actions), but doesn't explicitly differentiate from 'close' (which likely terminates a session).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a browser/page ID from 'browse'), exclusions, or contextual cues for choosing between extraction types. The agent must infer usage from parameter names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

interactC

Perform simple interactions on a page

ParametersJSON Schema
NameRequiredDescriptionDefault
browserIdYesBrowser ID from a previous browse operation
pageIdYesPage ID from a previous browse operation
actionYesThe type of interaction to perform
selectorYesCSS selector for the element to interact with
valueNoValue for fill/select actions

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'simple interactions' but doesn't specify what happens (e.g., page changes, errors, side effects), whether it's read-only or mutative, or any constraints like rate limits or authentication needs. This leaves significant gaps for a tool that performs actions on a page.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's front-loaded and clear in its brevity, though it could benefit from more detail to improve other dimensions. The structure is straightforward and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of performing interactions on a page (likely involving mutations), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, return values, or usage context, making it inadequate for safe and effective tool invocation by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as explaining how actions like 'click', 'fill', or 'select' work in context. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Perform simple interactions on a page', which provides a basic verb+resource combination but lacks specificity. It doesn't clarify what types of interactions beyond the generic term 'simple', nor does it distinguish this tool from potential siblings like 'extract' or 'browse'. The purpose is understandable but vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a browserId and pageId from a previous browse operation), exclusions, or comparisons to sibling tools like 'extract' or 'close'. Usage is implied through parameter names but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 4 tool updates
    • First observedbrowse
    • First observedclose
    • First observedextract
    • First observedinteract

TDQS

B3.3/5.0

Scored across 4 tools

Disambiguation4/5

The tools have mostly distinct purposes with clear boundaries: browse for navigation, extract for content retrieval, interact for actions, and close for cleanup. However, 'extract' and 'interact' could potentially overlap in some use cases (e.g., extracting after an interaction), but their descriptions help differentiate them.

Naming Consistency5/5

All tool names follow a consistent, simple verb-based pattern (browse, close, extract, interact) without any mixing of conventions. This makes the set predictable and easy to understand at a glance.

Tool Count5/5

With 4 tools, this server is well-scoped for its apparent purpose of web browsing and interaction. Each tool serves a clear, essential function, and there are no extraneous or redundant tools, making the count appropriate for the domain.

Completeness4/5

The toolset covers the core web browsing lifecycle: navigate (browse), retrieve content (extract), perform actions (interact), and clean up (close). A minor gap is the lack of explicit tools for handling multiple tabs or sessions, but agents can likely work around this with the provided tools.

Maintenance

ActivityInactive
ResponsivenessNo issues

Related MCP Connectors

Related MCP Servers

  • A
    license
    D
    quality
    D
    maintenance
    AI-driven browser automation server that implements the Model Context Protocol to enable natural language control of web browsers for tasks like navigation, form filling, and visual interaction.
    1
    2
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server that provides enhanced browser automation capabilities using Puppeteer-Extra with Stealth Plugin, enabling LLMs to interact with web pages in a way that better emulates human behavior and avoids detection as automation.
    3
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A Model Context Protocol server that enables AI assistants to interact with web pages through browser automation, supporting web scraping, form filling, navigation, and other browser-based tasks using Playwright.
    1
    MIT