Web Scraper MCP
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| scrapeA | Scrape a single URL into clean markdown (boilerplate/ads stripped). Tries a fast static fetch first and falls back to a stealth headless browser automatically when the page looks JS-gated. |
| extractB | Extract structured data (JSON matching json_schema) or a text answer from a page. |
| searchA | Web search. Returns ranked results (title, url, content snippet). |
| deep_researchA | Search the web, read the top sources, and return a cited synthesis report. |
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 4 tools
scrape and extract both operate on a page but are clearly distinguished by output type: markdown document vs structured JSON/answer. search and deep_research are also distinct, though deep_research could be seen as a superset of search.
All tools use lowercase snake_case imperative verbs: scrape, extract, search, deep_research. The naming pattern is consistent and predictable.
Four tools is well-scoped for a web scraper/research server: one for raw page content, one for structured extraction, one for search, and one for synthesis. Each tool has a clear purpose with no redundant bloat.
The core web research workflow is covered: search, fetch, extract, and synthesize. A minor gap is the lack of batch crawling or link-following features, but most common agent tasks can be completed with these tools.