Fetch MCP Server
Enables fetching web content and converting it to Markdown format, allowing for structured text representation of online resources.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Fetch MCP Server
This MCP server provides functionality to fetch web content in various formats, including HTML, JSON, plain text, and Markdown.
Tools
fetch_html
Fetch website content and return as HTML
Input parameters:
url(string, required): URL of the website to fetchheaders(object, optional): Custom headers to include in the request
Returns the raw HTML content of the webpage
fetch_json
Fetch JSON file from URL
Input parameters:
url(string, required): URL of the JSON to fetchheaders(object, optional): Custom headers to include in the request
Returns the parsed JSON content
fetch_txt
Fetch website content and return as plain text (no HTML)
Input parameters:
url(string, required): URL of the website to fetchheaders(object, optional): Custom headers to include in the request
Returns the text content of the webpage with HTML tags, scripts, and styles removed
fetch_markdown
Fetch website content and return as Markdown
Input parameters:
url(string, required): URL of the website to fetchheaders(object, optional): Custom headers to include in the request
Returns the webpage content converted to Markdown format
2 Ways to Start
bun
bun i
bun startdocker
docker compose up --build -dUsage
{
"mcpServers": {
"fetch-mcp": {
"transport": "sse",
"url": "http://localhost:3000/sse",
"headers": {
"Authorization": "Bearer your-token-here",
"X-Custom-Header": "custom-value"
},
"useNodeEventSource": true
}
}
}Resources
This server does not provide any persistent resources. It is designed to fetch and transform web content on demand.
References
This server cannot be deployed
Related MCP Connectors
Convert public web pages to PDF, images, Markdown, or JSON using one API key.
Turn any web page URL or HTML into clean Markdown or plain text for an LLM to read.
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Screenshot any URL/HTML as PNG/JPEG/WebP, or read it as clean Markdown/text for LLMs.
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