Fetch MCP Server
OfficialThe Fetch MCP Server enables web content fetching and processing for LLMs, with these capabilities:
Fetch web content: Retrieve content from any URL and convert it to markdown for easier consumption
Control content size: Specify maximum character limit to truncate responses
Chunked retrieval: Use
start_indexto fetch content incrementally for long web pagesRaw HTML access: Optionally retrieve content without markdown conversion
Customizable user-agent: Modify the user-agent string for requests
Proxy support: Configure the server to use a proxy for fetching content
Robots.txt handling: Respect or ignore
robots.txtrules based on configurationIntegration with LLMs: Designed to work seamlessly with models like Claude and VS Code
Click on "Deploy 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 article from techcrunch.com"
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.
Source: https://github.com/modelcontextprotocol/servers/tree/main/src/fetch
Requires MCP Python SDK 1.x (mcp>=1.29.0,<2). SDK 2.0 renamed APIs this server uses. The port to v2 is in progress.
This server can access local/internal IP addresses and may represent a security risk. Exercise caution when using this MCP server to ensure this does not expose any sensitive data.
By default the server refuses to fetch private, loopback, link-local and other non-public addresses, including cloud metadata endpoints such as 169.254.169.254, and checks every redirect hop the same way. The --allow-private-ips argument turns this guard off; see Customization - Private addresses. The guard checks the addresses a hostname resolves to before each request, so it does not protect against DNS rebinding between that check and the connection, and a hostname the server cannot resolve itself (one only a proxy can resolve) is not checked.
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)Annotations:
readOnlyHint: true,destructiveHint: false,idempotentHint: true,openWorldHint: true(it only reads, and it reaches arbitrary hosts on the internet)
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-fetchAfter installation, you can run it as a script using:
python -m mcp_server_fetchRelated MCP server: MCP Fetch
Configuration
Configure for Claude.app
Add to your Claude settings:
{
"mcpServers": {
"fetch": {
"command": "uvx",
"args": ["mcp-server-fetch"]
}
}
}{
"mcpServers": {
"fetch": {
"command": "docker",
"args": ["run", "-i", "--rm", "mcp/fetch"]
}
}
}{
"mcpServers": {
"fetch": {
"command": "python",
"args": ["-m", "mcp_server_fetch"]
}
}
}Configure for VS Code
For quick installation, use one of the one-click install buttons below...
For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).
Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.
Note that the
mcpkey is needed when using themcp.jsonfile.
{
"mcp": {
"servers": {
"fetch": {
"command": "uvx",
"args": ["mcp-server-fetch"]
}
}
}
}{
"mcp": {
"servers": {
"fetch": {
"command": "docker",
"args": ["run", "-i", "--rm", "mcp/fetch"]
}
}
}
}Customization - robots.txt
By default, the server will obey a websites robots.txt file if the request came from the model (via a tool), but not if
the request was user initiated (via a prompt). This can be disabled by adding the argument --ignore-robots-txt to the
args list in the configuration.
Customization - Private addresses
By default, the server refuses any request, including a redirect hop or a robots.txt fetch, whose host resolves to an
address that is not globally routable: loopback (127.0.0.0/8, ::1), private (10.0.0.0/8, 172.16.0.0/12,
192.168.0.0/16, fc00::/7), link-local (169.254.0.0/16, fe80::/10), shared address space (100.64.0.0/10),
multicast, unspecified, documentation and the other IANA special-purpose ranges. A hostname is refused if any one of its addresses is in those ranges.
The client receives an error naming the refused address.
To fetch from local or internal hosts (a development server, an intranet page), add the argument
--allow-private-ips to the args list in the configuration.
Customization - User-agent
By default, depending on if the request came from the model (via a tool), or was user initiated (via a prompt), the server will use either the user-agent
ModelContextProtocol/1.0 (Autonomous; +https://github.com/modelcontextprotocol/servers)or
ModelContextProtocol/1.0 (User-Specified; +https://github.com/modelcontextprotocol/servers)This can be customized by adding the argument --user-agent=YourUserAgent to the args list in the configuration.
Customization - Proxy
The server can be configured to use a proxy by using the --proxy-url argument.
Without --proxy-url, the server uses the proxy in the standard HTTP_PROXY, HTTPS_PROXY and ALL_PROXY
environment variables (honoring NO_PROXY). Both http(s):// and SOCKS5 proxies are supported (SOCKS support is
installed with the server). A socks:// proxy URL, as many desktop proxy settings export it, is treated as
socks5://. A proxy setting the server cannot use makes each fetch fail with a tool error that says so.
Windows Configuration
If you're experiencing timeout issues on Windows, you may need to set the PYTHONIOENCODING environment variable to ensure proper character encoding:
{
"mcpServers": {
"fetch": {
"command": "uvx",
"args": ["mcp-server-fetch"],
"env": {
"PYTHONIOENCODING": "utf-8"
}
}
}
}{
"mcpServers": {
"fetch": {
"command": "python",
"args": ["-m", "mcp_server_fetch"],
"env": {
"PYTHONIOENCODING": "utf-8"
}
}
}
}This addresses character encoding issues that can cause the server to timeout on Windows systems.
Debugging
You can use the MCP inspector to debug the server. For uvx installations:
npx @modelcontextprotocol/inspector uvx mcp-server-fetchOr if you've installed the package in a specific directory or are developing on it:
cd path/to/servers/src/fetch
npx @modelcontextprotocol/inspector uv run mcp-server-fetchDevelopment
From src/fetch:
uv sync --frozen --all-extras --dev
uv run --frozen pytestThe tests drive serve() through an MCP ClientSession in-process, with HTTP mocked, so they need no network. The HTML extraction tests need Node.js on PATH (readabilipy uses Readability.js when Node is present and a pure-Python fallback when it is not).
Coverage, measured per file with branch coverage:
uv run --frozen pytest --cov --cov-report=term-missing --cov-report=jsonThis writes coverage.json (git-ignored). The command reports coverage but does not enforce a threshold; the target is at least 90% of lines and 90% of branches for every file under src/mcp_server_fetch.
Contributing
We encourage contributions to help improve mcp-server-fetch. Bug reports, ideas for new tools, enhancements to existing functionality, and documentation improvements are all valuable.
For examples of other MCP servers and implementation patterns, see: https://github.com/modelcontextprotocol/servers
Contributions arrive as issues, not pull requests: the repository maintainers do the implementation. Open an issue with the bug report or feature request form, and if you have already prototyped a change, share the prompt you used rather than a diff. See CONTRIBUTING.md for the full policy.
License
mcp-server-fetch is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
Available Tools
1 toolfetchA
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 |
|---|---|---|---|
| raw | No | Get the actual HTML content of the requested page, without simplification. | |
| 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. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description partially covers behavior: it mentions fetching and markdown extraction but omits error handling, rate limits, or response truncation details. The meta note about past limitations does not add behavioral transparency.
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 brief with two sentences, front-loading the main action. The second sentence is slightly verbose but still concise overall.
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 no siblings or output schema, the description covers the core functionality and parameter usage adequately. It lacks mention of error scenarios but is sufficient for a fetch tool with well-defined schema.
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 coverage is 100%, so the description adds minimal value beyond parameter descriptions. It provides context by linking 'optionally extracts markdown' to the 'raw' parameter, but not enough to raise the score above baseline.
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 fetches a URL from the internet and optionally extracts markdown. It distinguishes this from any other tool by emphasizing internet access, and there are no siblings to differentiate.
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 tells the agent to use this tool for obtaining up-to-date internet information. Though lacking explicit when-not-to-use, the context of granting internet access implies its primary use case.
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.
1 tool update
v1.0.0- First observed
fetch
TDQS
Scored across 1 tool
With only one tool, there is no ambiguity for an agent to distinguish between tools.
The single tool is named 'fetch', a clear verb describing its action, and consistency is trivially maintained.
One tool is appropriate for a focused server dedicated to fetching URLs, covering its core purpose without unnecessary expansion.
The tool fetches a URL and optionally extracts markdown, but lacks support for other output formats or request customization, leaving some gaps for varied use cases.
Maintenance
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Document-to-Markdown MCP server — convert PDF, Office and HTML into LLM-ready Markdown.
Converts any URL to clean, LLM-ready Markdown using real Chrome browsers
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