ai-first-scraper-mcp
This server lets you fetch and search the web, returning clean, ad-free Markdown content ready for AI reasoning — no raw HTML parsing required.
fetch_page: Fetch a single URL (HTML or PDF) and return its main content as clean Markdown. Supports an optionalmax_tokenssoft cap to truncate large pages.fetch_pages_batch: Submit up to 25 URLs at once and fetch them in parallel. Each result includes metadata (title, word count, links) or an error if a URL failed — much faster than sequential calls.search_web: Run a free-text web search and automatically retrieve the top-k result pages (1–10, default 5) already converted to Markdown. Each result includes the URL, title, snippet, and full Markdown content, making it easy to find, evaluate, and cite fresh information in one call.
ai-first-scraper-mcp
Plug Claude Desktop, Cursor, or Cline straight into an ad-free web scraper + search engine. Three tools, one line of config.
What it does
Adds three tools to any MCP-compatible agent:
Tool | What it does |
| Fetch one URL → return clean Markdown (HTML or PDF). |
| Fetch up to 25 URLs in parallel → return Markdown for each. |
| Run a web search and return the top-k result pages already converted to Markdown. |
No more "the model called curl and then tried to parse 80kB of ad HTML." Your agent receives clean Markdown ready to reason about.
Backed by the ai-first-scraper and ai-first-search APIs.
Related MCP server: CC Web MCP
Install
Fastest — uvx (no install, runs from PyPI on demand)
// claude_desktop_config.json / cline_mcp_settings.json / ~/.cursor/mcp.json
{
"mcpServers": {
"ai-first-scraper": {
"command": "uvx",
"args": ["ai-first-scraper-mcp"]
}
}
}Restart your client (Claude Desktop / Cursor / Cline). The three tools above will appear automatically.
Alternative — pip install
pip install ai-first-scraper-mcp{
"mcpServers": {
"ai-first-scraper": {
"command": "ai-first-scraper-mcp"
}
}
}Where the config file lives
Client | Config path |
Claude Desktop (macOS) |
|
Claude Desktop (Windows) |
|
Cursor |
|
Cline (VS Code) |
|
Point at your own backend (optional)
By default this server calls the public ai-first-scraper.onrender.com and
ai-first-search.onrender.com instances. If you want to self-host, set env
vars in your MCP config:
{
"mcpServers": {
"ai-first-scraper": {
"command": "uvx",
"args": ["ai-first-scraper-mcp"],
"env": {
"SCRAPER_URL": "https://your-scraper.example.com",
"SEARCH_URL": "https://your-search.example.com",
"AFS_TIMEOUT": "60"
}
}
}
}Verify it works
Open your MCP client and ask the agent:
"Use the search_web tool to find the top 3 recent articles about MCP and summarize them in 5 bullets each."
You should see the agent call search_web, get back Markdown for each result,
and produce the summary without ever touching raw HTML.
Companion projects
ai-first-scraper — the per-URL Markdown cleaner this MCP server fans out to.
ai-first-search — search → scrape → markdown pipeline.
mcp-rec — record & replay any MCP server's traffic for tests and bug reports.
llm-cache-proxy — local cache for OpenAI/Anthropic API calls.
promptlocker — lockfile for prompts.
context-diff — see what blew up your Claude Code context window.
agentwatch — overlay for browser AI agents.
Develop locally
git clone https://github.com/yubinkim444/ai-first-scraper-mcp.git
cd ai-first-scraper-mcp
uv sync # or: pip install -e .
ai-first-scraper-mcp # speaks MCP over stdioTo test against a local client, point its MCP config at the same command.
About the author
Built by yubinkim444, who also makes Kay's Records — an app for iOS and Android.
If this project saved you time, giving the app a try is the nicest way to say thanks.
License
MIT © yubinkim444
Available Tools
3 toolsfetch_pageA
Fetch a single web page or PDF and return its main content as clean, ad-free Markdown — ready to drop into an LLM prompt.
Args:
url: A fully-qualified http(s) URL.
max_tokens: Optional soft cap on the returned Markdown (whitespace
tokens). When exceeded, the body is truncated and a
[...truncated] marker is appended.
Returns: The cleaned Markdown body of the page.
Inputs: url (required), max_tokens. Returns: result
fetch_pages_batchA
Fetch many web pages in parallel and return each one's clean Markdown.
Use this whenever you need to read more than one URL at once — it is far faster than calling fetch_page in a loop because the upstream scraper handles the concurrency.
Args: urls: Up to 25 URLs. max_tokens: Optional per-URL soft cap on the returned Markdown.
Returns:
A list of {url, ok, data?, error?} objects in the same order as the
input URLs. data is {title, word_count, markdown, links, ...} on
success; error contains the failure reason otherwise.
Inputs: urls (required), max_tokens. Returns: result
search_webA
Run a web search and return the top-k result pages already converted to clean Markdown. Use this whenever you need fresh information from the public web — it combines search and read in one call.
Args: q: The user's query (free text). k: How many results to fetch (1–10, default 5). max_tokens: Optional per-result soft cap on the returned Markdown.
Returns:
A list of {url, title, snippet, ok, markdown, word_count, error?}
result objects. Use title and snippet to decide which results are
worth citing, then drop the markdown field into your prompt.
Inputs: q (required), k, max_tokens. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: single page fetch, batch fetch, and web search. No overlap; agents can easily distinguish them.
All tool names follow a consistent verb_noun snake_case pattern: fetch_page, fetch_pages_batch, search_web. The slight singularity/plural variation is minor and predictable.
Three tools perfectly scope a scraping-focused server: single page, batch, and search. Neither too many nor too few for the domain.
The tool surface fully covers the core scraping workflow (fetch single, batch, search). No obvious gaps given the stated purpose of returning clean Markdown.
Maintenance
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