MCP server for advanced search and retrieval of web crawler data supporting multiple crawler formats.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Server Webcrawl.
Website | GitHub | Docs | PyPi
Advanced search and retrieval for web crawler data. With mcp-server-webcrawl, your AI client filters and analyzes web content under your direction or autonomously. The server includes a fulltext search interface with boolean support, and resource filtering by type, HTTP status, and more.
mcp-server-webcrawl provides the LLM a complete menu with which to search, and works with a variety of web crawlers:
| Crawler/Format | Description | Platforms | Setup Guide |
|---|---|---|---|
| ArchiveBox | Web archiving tool | macOS/Linux | Setup Guide |
| HTTrack | GUI mirroring tool | macOS/Windows/Linux | Setup Guide |
| InterroBot | GUI crawler and analyzer | macOS/Windows/Linux | Setup Guide |
| Katana | CLI security-focused crawler | macOS/Windows/Linux | Setup Guide |
| SiteOne | GUI crawler and analyzer | macOS/Windows/Linux | Setup Guide |
| WARC | Standard web archive format | varies by client | Setup Guide |
| wget | CLI website mirroring tool | macOS/Linux | Setup Guide |
mcp-server-webcrawl is free and open source, and requires Claude Desktop and Python (>=3.10). It is installed on the command line, via pip install:
For step-by-step MCP server setup, refer to the Setup Guides.
mcp-server-webcrawl provides the toolkit necessary to search web crawl data freestyle, figuring it out as you go, reacting to each query. This is what it was designed for.
It is also capable of running routines (as prompts). You can write these yourself, or use the ones provided. These prompts are copy and paste, and used as raw Markdown. They are enabled by the advanced search provided to the LLM; queries and logic can be embedded in a procedural set of instructions, or even an input loop as is the case with Gopher Service.
| Prompt | Download | Category | Description |
|---|---|---|---|
| π SEO Audit | auditseo.md | audit | Technical SEO (search engine optimization) analysis. Covers the basics, with options to dive deeper. |
| π 404 Audit | audit404.md | audit | Broken link detection and pattern analysis. Not only finds issues, but suggests fixes. |
| β‘Β PerformanceΒ Audit | auditperf.md | audit | Website speed and optimization analysis. Real talk. |
| π File Audit | auditfiles.md | audit | File organization and asset analysis. Discover the composition of your website. |
| π Gopher Interface | gopher.md | interface | An old-fashioned search interface inspired by the Gopher clients of yesteryear. |
| βοΈ Search Test | testsearch.md | self-test | A battery of tests to check for Boolean logical inconsistencies in the search query parser and subsequent FTS5 conversion. |
If you want to shortcut the site selection (one less query), paste the markdown and in the same request, type "run pasted for [site name or URL]." It will figure it out. When pasted without additional context, you should be prompted to select from a list of crawled sites.
The query engine supports field-specific (field: value) searches and complex boolean expressions. Fulltext is supported as a combination of the url, content, and headers fields.
While the API interface is designed to be consumed by the LLM directly, it can be helpful to familiarize yourself with the search syntax. Searches generated by the LLM are inspectable, but generally collapsed in the UI. If you need to see the query, expand the MCP collapsible.
Example Queries
| Query Example | Description |
|---|---|
| privacy | fulltext single keyword match |
| "privacy policy" | fulltext match exact phrase |
| boundar* | fulltext wildcard matches results starting with boundar (boundary, boundaries) |
| id: 12345 | id field matches a specific resource by ID |
| url: example.com/somedir | url field matches results with URL containing example.com/somedir |
| type: html | type field matches for HTML pages only |
| status: 200 | status field matches specific HTTP status codes (equal to 200) |
| status: >=400 | status field matches specific HTTP status code (greater than or equal to 400) |
| content: h1 | content field matches content (HTTP response body, often, but not always HTML) |
| headers: text/xml | headers field matches HTTP response headers |
| privacy AND policy | fulltext matches both |
| privacy OR policy | fulltext matches either |
| policy NOT privacy | fulltext matches policies not containing privacy |
| (login OR signin) AND form | fulltext matches fulltext login or signin with form |
| type: html AND status: 200 | fulltext matches only HTML pages with HTTP success |
Field search provides search precision, allowing you to specify which columns of the search index to filter. Rather than searching the entire content, you can restrict your query to specific attributes like URLs, headers, or content body. This approach improves efficiency when looking for specific attributes or patterns within crawl data.
| Field | Description |
|---|---|
| id | database ID |
| url | resource URL |
| type | enumerated list of types (see types table) |
| size | file size in bytes |
| status | HTTP response codes |
| headers | HTTP response headers |
| content | HTTP bodyβHTML, CSS, JS, and more |
A subset of fields can be independently requested with results, while core fields are always on. Use of headers and content can consume tokens quickly. Use judiciously, or use extras to crunch more results into the context window. Fields are a top level argument, independent of any field searching taking place in the query.
| Field | Description |
|---|---|
| id | always available |
| url | always available |
| type | always available |
| status | always available |
| created | on request |
| modified | on request |
| size | on request |
| headers | on request |
| content | on request |
Crawls contain resource types beyond HTML pages. The type: field search allows filtering by broad content type groups, particularly useful when filtering images without complex extension queries. For example, you might search for type: html NOT content: login to find pages without "login," or type: img to analyze image resources. The table below lists all supported content types in the search system.
| Type | Description |
|---|---|
| html | webpages |
| iframe | iframes |
| img | web images |
| audio | web audio files |
| video | web video files |
| font | web font files |
| style | CSS stylesheets |
| script | JavaScript files |
| rss | RSS syndication feeds |
| text | plain text content |
| PDF files | |
| doc | MS Word documents |
| other | uncategorized |
The extras parameter provides additional processing options, transforming HTTP data (markdown, snippets, regex, xpath), or connecting the LLM to external data (thumbnails). These options can be combined as needed to achieve the desired result format.
| Extra | Description |
|---|---|
| thumbnails | Generates base64 encoded images to be viewed and analyzed by AI models. Enables image description, content analysis, and visual understanding while keeping token output minimal. Works with images, which can be filtered using type: img in queries. SVG is not supported. |
| markdown | Provides the HTML content field as concise Markdown, reducing token usage and improving readability for LLMs. Works with HTML, which can be filtered using type: html in queries. |
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