MCP Browser Text Reader
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_page_textC | 获取指定URL页面的文本内容 |
| get_current_page_textC | 获取当前浏览器页面的文本内容 |
| navigate_to_pageC | 导航到指定URL |
| get_page_infoB | 获取当前页面的基本信息（标题、URL等） |
| close_browserC | 关闭浏览器实例 |
| launch_chrome_manuallyB | 手动启动Chrome浏览器（可见窗口） |
| get_browser_statusB | 获取浏览器连接状态 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Most tools have distinct purposes, such as launching, navigating, getting text, and closing. However, 'get_current_page_text' and 'get_page_text' could cause confusion: the former targets the current page, while the latter targets a specified URL, but their names and descriptions are similar enough that an agent might misselect them without careful reading.
All tool names follow a consistent snake_case pattern with clear verb_noun structures (e.g., 'close_browser', 'get_page_text'). There are no deviations in naming conventions, making the set predictable and easy to parse for an agent.
With 7 tools, this server is well-scoped for its purpose of reading text from a browser. It covers essential operations like launching, navigating, retrieving text and info, and closing, without being overly sparse or bloated, which is appropriate for the domain.
The tool set covers core workflows for browser text reading, including launching, navigation, text retrieval, and cleanup. A minor gap is the lack of tools for interacting with page elements (e.g., clicking, inputting text) or handling errors, but agents can still perform basic text extraction tasks effectively.