Jina_fetch
@RoadMillion
About Jina_fetch
Convert url to LLM-friendly text, powered by jina ai reader
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"jina_fetch": {
"isActive": true,
"command": "uvx",
"args": [
"mcp-jina-reader@latest"
]
}
}
}Tools
1Use Jina URL reader to process URLs and return LLM-friendly output
Overview
What is Jina_fetch?
Jina_fetch is a standard MCP server that converts URLs into LLM-friendly inputs using Jina AI's API. It is designed for developers who need to feed web content into large language models.
How to use Jina_fetch?
Install by adding the server configuration to your Claude Desktop config file (MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json, Windows: %APPDATA%/Claude/claude_desktop_config.json). Use the reader tool with a mandatory url string parameter to process a URL and return its content.
Key features of Jina_fetch
- Converts URLs into LLM-friendly text
- Uses Jina AI's URL reader API
- Single tool with one required parameter
- Standard MCP server for easy integration
- Supports development and published deployment
Use cases of Jina_fetch
- Feeding web page content into an LLM for summarization
- Extracting readable text from URLs for analysis
- Providing context from online sources to AI assistants
FAQ from Jina_fetch
What does Jina_fetch do?
It takes a URL as input and returns the processed content in a format suitable for large language models, using Jina AI's API.
What are the runtime requirements?
Jina_fetch requires Python and the uv package manager. It can be run via uv (development) or uvx (published).
Where does the data go?
The URL is sent to Jina AI's API for processing; the returned content is delivered back to the MCP client.
What transport does Jina_fetch use?
It communicates over stdio, as is standard for MCP servers.
Are there any known limits?
The README does not specify any limits.
Frequently asked questions
What does Jina_fetch do?
It takes a URL as input and returns the processed content in a format suitable for large language models, using Jina AI's API.
What are the runtime requirements?
Jina_fetch requires Python and the `uv` package manager. It can be run via `uv` (development) or `uvx` (published).
Where does the data go?
The URL is sent to Jina AI's API for processing; the returned content is delivered back to the MCP client.
What transport does Jina_fetch use?
It communicates over stdio, as is standard for MCP servers.
Are there any known limits?
The README does not specify any limits.
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