ReviewWebsite.com - MCP Server
About
TypeScript Model Context Protocol (MCP) server for ReviewWebsite. Includes CLI support and extensible structure for connecting AI systems (LLMs) to ReviewWeb.site API
Details
- License
- MIT
Explore
- [x] Create, read, update, and delete website reviews
- [x] Get available AI models
- [x] Convert URLs to Markdown using AI
- [x] Extract structured data from URLs using AI
- [x] Scrape URLs and extract content
- [x] Extract links from websites
- [x] Summarize URLs and websites using AI
- [x] SEO insights (keyword ideas, keyword difficulty, traffic analysis, backlinks)
- [x] Customize AI models and parameters
- [x] Control wait behavior and timing
- Node.js (>=18.x): Download
- Git: For version control
---
For local configuration with stdio transport:
{
"mcpServers": {
"reviewwebsite": {
"command": "node",
"args": ["/path/to/reviewwebsite-mcp-server/dist/index.js"],
"transportType": "stdio"
}
}
}
For remote HTTP configuration:
{
"mcpServers": {
"reviewwebsite": {
"type": "http",
"url": "http://localhost:8080/mcp"
}
}
}
Environment Variables for HTTP Transport:
You can configure the HTTP server using these environment variables:
- MCP_HTTP_HOST: The host to bind to (default: 127.0.0.1)
- MCP_HTTP_PORT: The port to listen on (default: 8080)
- MCP_HTTP_PATH: The endpoint path (default: /mcp)
---
npm install
---
DEBUG=true npm run dev:server
```
---
Use the ReviewWebsite API tools via CLI:
- Purpose: Define MCP tools with schemas and descriptions for AI assistants
- Naming: Files should be named <feature>.tool.ts with types in <feature>.types.ts
- Pattern: Each tool should use zod for argument validation
Follow these steps to add your own tools to the server:
Create a tool definition in src/tools/:
typescript// src/tools/example.tool.ts
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import { z } from 'zod';
import { Logger } from '../utils/logger.util.js';
import { formatErrorForMcpTool } from '../utils/error.util.js';
import * as exampleController from '../controllers/example.controller.js';
const logger = Logger.forContext('tools/example.tool.ts');
const GetDataArgs = z.object({
param: z.string().optional().describe('Optional parameter'),
});
type GetDataArgsType = z.infer<typeof GetDataArgs>;
async function handleGetData(args: GetDataArgsType) {
try {
logger.debug('Tool get_data called', args);
const result = await exampleController.getData({
param: args.param,
});
return {
content: [{ type: 'text' as const, text: result.content }],
};
} catch (error) {
logger.error('Tool get_data failed', error);
return formatErrorForMcpTool(error);
}
}
export function register(server: McpServer) {
server.tool(
'get_data',
Gets data from the example API, optionally using \param\.,
Use this to fetch example data. Returns formatted data as Markdown.
GetDataArgs.shape,
handleGetData,
);
}
```
This project provides a Model Context Protocol (MCP) server that connects AI assistants to ReviewWebsite.com API to create and manage website reviews, extract data, convert URLs to markdown, and more.
<a href="https://glama.ai/mcp/servers/@mrgoonie/reviewwebsite-mcp-server">
</a>
Available Features
- [x] Create, read, update, and delete website reviews - [x] Get available AI models - [x] Convert URLs to Markdown using AI - [x] Extract structured data from URLs using AI - [x] Scrape URLs and extract content - [x] Extract links from websites - [x] Summarize URLs and websites using AI - [x] SEO insights (keyword ideas, keyword difficulty, traffic analysis, backlinks) - [x] Customize AI models and parameters - [x] Control wait behavior and timingReviewWeb.site
- Website
- API Docs
- API Swagger Config
- Create your API key here
Supported Transports
- [x] "stdio" transport - Default transport for CLI usage
- [x] "Streamable HTTP" transport - For web-based clients
- [ ] Implement auth ("Authorization" headers with Bearer <token>)
- [ ] ~~"sse" transport~~ (Deprecated)
- [ ] Write tests
How to use
CLI
```bash
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