Fetches public posts from a subreddit via the official Reddit API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Wafle-Scraper scrape the front page of Hacker News"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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╚══╝╚══╝ ╚═╝ ╚═╝ ╚═╝ ╚══════╝╚══════╝Wafle-Scraper is an MCP server that lets AI agents (OpenCode, Claude, Cursor) extract data from the web safely and responsibly.
Rule | Enforcement |
No private data | Every browser session is incognito — no cookies, no localStorage, no saved passwords |
Only what you ask | The scraper never mines extra data beyond your explicit request |
No localhost | Internal/private IPs are blocked by default |
Rate limited | Minimum 2 seconds between requests — never floods servers |
CAPTCHA = human only | No automated CAPTCHA solving. If one appears, you solve it interactively |
User-Agent rotation | Each request looks like a real browser |
Related MCP server: sessemi-mcp
pip install wafle-scraper
playwright install chromium
wafle-scraper{
"mcpServers": {
"wafle-scraper": {
"command": "wafle-scraper",
"description": "Web scraping & browser automation — incognito, audited, safe"
}
}
}wafle-scraper # MCP stdio mode (default for agents)
wafle-scraper --http --port 8000 # HTTP SSE mode
wafle-scraper --version # Show versionTool | Description | Safety |
| Extract text from a static URL (requests + BeautifulSoup) | ✅ Read-only, no JS |
| Navigate a page in isolated incognito browser and extract text | ✅ Incognito, no cookies |
| Fetch public posts from a subreddit via official API | ✅ API, no scraping |
| Find email addresses on a public page | ✅ Only what you ask |
| Click, type, scroll, extract, screenshot in live browser | ✅ You control the actions |
Incognito always: storage_state=None, fresh context per session
No permissions: No camera, mic, location access
Anti-detection: Rotating UA, viewport, locale, timezone
Natural delays: Human-like timing between actions
Gradual scroll: Loads lazy content naturally
Wafle-Scraper does NOT solve CAPTCHAs automatically. When a CAPTCHA is detected:
The scraper pauses
Prompts you to open the URL in your browser
You solve the CAPTCHA manually
Type done and the scraper continues
This is the only ethical and reliable approach without paid services.
Blocked: localhost, 127.0.0.1, private IPs, file://, chrome://
Rate limiting (configurable, default 2s min interval)
Scope enforcement — only processes what you explicitly request
User-Agent rotation
Browser isolation — Playwright contexts are fully sandboxed
Python 3.10+
Playwright with Chromium installed (playwright install chromium)
Windows, macOS, Linux
Standalone — no other MCP servers required.
Issue | Detail | Status |
CDP health check unstable |
| 🟡 Medium |
CAPTCHA handler is interactive only | CAPTCHA solver relies on stdin — doesn't work in MCP server mode (no stdin available in stdio transport). | 🔴 High |
| No exponential backoff, no proxy fallback. If 2 attempts fail, the whole scrape fails. | 🟡 Medium |
Error strings instead of exceptions |
| 🟡 Medium |
Single browser context | Only 1 context at a time. Concurrent | 🔴 High |
Reddit HTML fallback is silent | If JSON API fails, falls back to | 🟢 Low |
git clone https://github.com/creandoaldia/wafle-scraper.git
cd wafle-scraper
pip install -e .
playwright install chromiumMIT
Part of the WAFLE ecosystem (Web AI Framework for Language Ecosystems). Wafle-Scraper gives WAFLE agents the ability to read the live web — safely, transparently, and under your control.
Interact with the active browser page (click, type, extract).
| Name | Required | Description | Default |
|---|---|---|---|
| value | No | ||
| action | Yes | ||
| selector | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions actions but does not indicate that clicking/typing are mutational, whether modifications are reversible, or the need for page focus. Output schema exists but return values are not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, but it is under-specified rather than concise; it lacks critical details about parameter usage and behavior, making it inefficient for an agent to use correctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters, no annotation support, and no parameter descriptions, the description fails to provide essential context. It does not cover how to specify actions, query selectors, or input values, leaving the agent to guess.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It lists 'click, type, extract' but does not map them to the 'action' parameter, nor explain the meaning of 'selector' and 'value' in relation to these actions. Parameter semantics are entirely absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'Interact' and lists example actions (click, type, extract), making it clear that this tool manipulates the active browser page. It distinguishes from sibling tools like scrape_browser which are read-only scraping.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, nor any prerequisites or limitations (e.g., when to prefer a specific sibling tool). The description is purely functional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find email addresses on a public page.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full transparency burden. It states the tool 'finds' emails on a 'public page' but does not disclose how it works (e.g., HTTP request vs local parsing), whether authentication is needed, or any limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence that front-loads the verb. It is appropriately sized with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description is adequate but minimal. It could add behavioral context (e.g., 'Extracts all anchor text' or 'Results include email addresses found in visible HTML').
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must add meaning. It clarifies that the 'url' parameter refers to a public page, but adds no further syntax or format details. For a single parameter, this is minimally helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Find email addresses on a public page' uses a specific verb and resource, clearly indicating the tool's function. It distinguishes itself from sibling tools like 'scrape_url' (general scraping) and 'scrape_reddit' (platform-specific), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. Given sibling tools like 'scrape_url' may also extract emails, lack of usage context makes it harder for an agent to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Navigate a page in an isolated incognito browser and extract text.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| scroll | No | ||
| wait_selector | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions 'isolated incognito browser' implying privacy, but does not explain JavaScript handling, error behavior, or return format. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 9 words, front-loaded with the core action. However, given the tool's complexity (3 parameters, output schema), it is too brief to be fully informative, balancing conciseness with substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not cover parameter usage, output format, or behavioral details. With no annotations and low schema coverage, the description is insufficient for an agent to use the tool correctly without additional inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does not explain the 'scroll' or 'wait_selector' parameters beyond their names, which are somewhat self-explanatory but lack context (e.g., scroll for dynamic loading, wait_selector for element visibility).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Navigate a page in an isolated incognito browser and extract text,' which clearly identifies the tool's main action and resource. It distinguishes from siblings like 'browser_interact' (which likely involves interaction) and 'scrape_reddit' (site-specific), though the term 'extract text' could be more specific about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'scrape_url' or 'browser_interact'. The description lacks any context about prerequisites, scenarios, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch public posts from a subreddit via the official Reddit API.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | hot | |
| limit | No | ||
| subreddit | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only notes 'public posts' implying read-only, but fails to disclose rate limits, authentication needs, error handling, pagination, or other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and to the point. Could include more detail without being verbose, but structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is low complexity with 3 parameters and an output schema reducing burden. However, description lacks usage guidelines and parameter details, making it only adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no explanation of sort or limit parameters beyond their names and defaults. Does not compensate for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Fetch', resource 'public posts from a subreddit', and method 'via the official Reddit API'. This distinguishes it from sibling tools like scrape_browser which use different scraping approaches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for fetching Reddit posts, but no explicit guidance on when to use vs alternatives like scrape_browser or scrape_url, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Extract readable text content from a static URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| extract_links | No | ||
| extract_images | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states 'static URL' and 'extract readable text content'. It fails to disclose important behaviors like handling of redirects, error states, or any limitations beyond the static nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous content, front-loading the core purpose efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 3 parameters and an output schema, the description does not explain the optional extraction behaviors or the format of the output. It lacks sufficient detail for an agent to fully understand the tool's capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, meaning the description adds no meaning to the parameters. It does not mention the optional extract_links or extract_images flags, leaving the agent to infer their purpose solely from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Extract' and the resource 'readable text content from a static URL', clearly distinguishing it from sibling tools like 'scrape_browser' (dynamic content) and 'browser_interact' (interactive browsing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'scrape_browser' or 'browser_interact'. The description does not mention any preconditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0browser_interactextract_emailsscrape_browserscrape_redditscrape_urlMost tools have clear purposes: extract_emails, scrape_reddit, and scrape_url are distinct. However, browser_interact and scrape_browser both involve browser interaction, potentially causing confusion despite different contexts (active page vs. isolated browser).
Tools use snake_case but mix patterns: 'browser_interact' is noun_verb, while others like 'extract_emails' and 'scrape_browser' are verb_noun. The inconsistent placement of 'browser' in two tool names adds confusion.
With 5 tools, the server covers static scraping, browser scraping, interaction, email extraction, and Reddit API access. This is a well-scoped set for a scraping-focused server.
The tool set covers core scraping needs: static URLs, dynamic pages, specific platform (Reddit), email extraction, and interaction. Minor gaps like handling pagination or form submission exist but are acceptable for this scope.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
Web scraping for AI agents. Extract text and metadata from any URL worldwide. $0.005/page.
Reliable web access for AI agents: smart HTTP, rotating proxies, and full-browser rendering.
Enable language models to perform advanced AI-powered web scraping with enterprise-grade reliabili…
Live web access for agents: scrape, SERP search, crawl/map, 74 collectors, datasets, proxies.
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