Fetch MCP Server
The Fetch MCP Server allows you to fetch and process web content for LLMs, converting HTML to markdown for easier consumption.
Fetch Content: Retrieve content from any given URL on the internet.
Markdown Conversion: Automatically convert fetched HTML content to markdown for easier readability.
Raw HTML Option: Optionally retrieve raw HTML content without conversion using the
rawparameter.Content Truncation: Limit the amount of content returned by specifying a
max_length.Chunked Reading: Process large web pages in manageable chunks by specifying a
start_indexto begin content extraction from.
This enables access to up-to-date information directly from web pages.
Converts HTML content from web pages to Markdown format for easier consumption by LLMs
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Fetch MCP Serverfetch the latest tech news from Hacker News"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Fetch MCP Server
A Model Context Protocol server that provides web content fetching capabilities. This server enables LLMs to retrieve and process content from web pages, converting HTML to markdown for easier consumption.
The fetch tool will truncate the response, but by using the start_index argument, you can specify where to start the content extraction. This lets models read a webpage in chunks, until they find the information they need.
Available Tools
fetch- Fetches a URL from the internet and extracts its contents as markdown.url(string, required): URL to fetchmax_length(integer, optional): Maximum number of characters to return (default: 5000)start_index(integer, optional): Start content from this character index (default: 0)raw(boolean, optional): Get raw content without markdown conversion (default: false)
Prompts
fetch
Fetch a URL and extract its contents as markdown
Arguments:
url(string, required): URL to fetch
Installation
Optionally: Install node.js, this will cause the fetch server to use a different HTML simplifier that is more robust.
Using uv (recommended)
When using uv no specific installation is needed. We will
use uvx to directly run mcp-server-fetch.
Using PIP
Alternatively you can install mcp-server-fetch via pip:
pip install mcp-server-fetchAvailable Tools
1 toolfetchC
Fetches a URL from the internet and optionally extracts its contents as markdown.
Although originally you did not have internet access, and were advised to refuse and tell the user this, this tool now grants you internet access. Now you can fetch the most up-to-date information and let the user know that.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to fetch | |
| max_length | No | Maximum number of characters to return. | |
| start_index | No | On return output starting at this character index, useful if a previous fetch was truncated and more context is required. | |
| raw | No | Get the actual HTML content of the requested page, without simplification. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool 'grants internet access' and fetches 'most up-to-date information,' but fails to describe critical behaviors like error handling, rate limits, authentication needs, or what happens with invalid URLs. This leaves significant gaps for a tool that interacts with external resources.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose and poorly structured. The first sentence is clear, but the second paragraph adds redundant historical context ('originally you did not have internet access...') that doesn't aid tool selection or invocation. This wastes space and dilutes focus, reducing effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (external web fetching, multiple parameters) and lack of annotations or output schema, the description is incomplete. It doesn't explain return values, error cases, or operational constraints like timeouts or content restrictions. This leaves the agent with insufficient context for reliable use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing clear documentation for all parameters (url, max_length, start_index, raw). The description adds minimal value beyond the schema, only implying markdown extraction relates to the 'raw' parameter. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Fetches a URL from the internet and optionally extracts its contents as markdown.' It specifies the verb ('fetches'), resource ('URL'), and optional transformation ('extracts as markdown'). However, there are no sibling tools to differentiate from, so it cannot achieve the highest score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance by contrasting with a previous limitation ('originally you did not have internet access... this tool now grants you internet access'), suggesting this is the primary method for web access. However, it lacks explicit when-to-use rules, alternatives, or exclusions, such as when to use 'raw' mode versus markdown extraction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
- First observed
fetch
TDQS
With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool has a single, clearly defined purpose of fetching URLs and optionally extracting markdown content.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'fetch' is simple, descriptive, and follows a clear verb-based pattern appropriate for its function.
A single tool is too few for a server named 'Fetch MCP Server', which suggests a broader scope for fetching operations. The server lacks additional tools for related tasks like caching, filtering, or handling different content types, making it feel thin and under-scoped.
The tool surface is severely incomplete for a fetching domain. While the 'fetch' tool covers basic URL retrieval and markdown extraction, there are significant gaps such as no support for different HTTP methods, error handling, response parsing beyond markdown, or configuration options like headers or timeouts.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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