Fetch MCP Server
OfficialFetch MCP Server lets an LLM retrieve web content from URLs and return it as simplified markdown or raw HTML.
Fetch any URL (subject to configured robots.txt, private-IP, and host allowlist restrictions).
Convert HTML pages into markdown for easier model consumption.
Retrieve raw HTML instead of simplified markdown when needed.
Limit response length with
max_lengthand continue reading withstart_index.Set a per-call HTTP timeout via
timeout_ms.Use the
fetchprompt for user-initiated URL fetching.Respect content negotiation and return markdown directly when a site provides it.
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 2.x (mcp>=2.3,<3).
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.
The markdown of an HTML page opens with the page's title as a # heading (its og:title, else its <h1> when the <title> holds it, else its <title> or <h1>), because the extraction drops a heading that repeats the title. It is not added when the markdown already opens with it, to a raw result, or to a page that failed to simplify.
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)timeout_ms(integer, optional): HTTP request timeout for this call, in milliseconds, from 100 to 600000 (default: the server's timeout, 30000 unless configured; see Customization - Timeout)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
Errors
A failed fetch (a robots.txt refusal, an unreachable page, an HTTP error status, a refused private address, an unusable proxy setting) and arguments that do not match the tool's schema are returned as a tool result with
isError: true, whose text startsError executing tool fetch:and says what went wrong, so the model can read it and decide what to do.Calling a tool the server does not have is a JSON-RPC protocol error,
-32602(Unknown tool: <name>), as the specification requires. So is getting a prompt it does not have (Unknown prompt: <name>), or thefetchprompt without itsurl(URL is required) or with aurlthat is not a valid URL (Invalid URL '<url>': <reason>).When the
fetchprompt's fetch fails, the prompt still returns: its message holds the reason the fetch failed.
The server is built on the MCP Python SDK's high-level MCPServer: the tool and the prompt are decorated functions, and their type hints and field descriptions are the input schema and the prompt's arguments.
Content negotiation
The tool and the prompt ask for markdown first, with the request header Accept: text/markdown, text/html;q=0.9, */*;q=0.8. A site that serves markdown through content negotiation sends it directly, and a text/markdown response is returned as-is: it is not simplified and carries no raw-content notice. A site that ignores the header sends what it always did, and HTML is simplified to markdown as before. A raw fetch keeps the default Accept: */*, so it gets whatever the site serves by default (for a web page, its HTML), unsimplified; a markdown response it receives anyway is returned as-is too.
Protocol versions
The server speaks both eras of the Model Context Protocol over stdio, with nothing to configure: a 2026-07-28 client (discovered with server/discover, no session) and a 2025-11-25 client (the initialize handshake). The client's first request decides which. Tools and prompts behave the same in both. Methods the 2026-07-28 specification removes, such as ping, are answered only on a 2025-11-25 connection.
Installation
Optionally: Install node.js, this will cause the fetch server to use a different HTML simplifier that is more robust. Its JavaScript dependencies are then installed with npm on first use, which contacts the npm registry. To keep the server from ever starting Node.js, see Customization - HTML extraction.
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). Every redirect hop of a tool fetch is checked against the robots.txt of
the host it leads to, the same way as the requested URL. If the robots.txt request fails to connect, or is answered
with 401, 403 or a server error (5xx), the tool refuses the fetch rather than reading the response as rules (RFC 9309
treats a 5xx robots.txt as complete disallow); any other 4xx is treated as no rules. 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. An IPv4-mapped (::ffff:0:0/96) or
well-known NAT64 (64:ff9b::/96) address is judged by the IPv4 address it carries; a deprecated IPv4-compatible
address (::/96, such as ::127.0.0.1) is refused whatever IPv4 it carries. 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 - Allowed hosts
By default the server may fetch from any host (subject to the private-address guard above). To restrict it to the
hosts you name, add --allowed-hosts followed by one or more entries to the args list (the argument can also be
repeated). Each entry is one of:
an exact host name, such as
docs.python.org, which matches that host only, not its subdomains;*.followed by a domain, such as*.github.com, which matches every subdomain of it at any depth (api.github.com,a.b.github.com) but notgithub.comitself: list both to allow both;an IP address, such as
203.0.113.7or2001:db8::7, which matches a URL that uses that address literally.
Matching ignores case and a trailing dot, and an internationalized name may be given in either its Unicode or its
xn-- form. An entry names a host only, so it carries no scheme, port or path. The list is checked before every request
the server sends, by the host name in the URL rather than by the addresses it resolves to: the requested page, its
robots.txt check, and every redirect hop of either, from the tool and from the prompt alike. A request to any other host
is refused before it is sent, and the client receives an error naming the refused host.
The allowlist and the private-address guard are separate checks, and a request must pass both. Listing an internal
host, such as localhost or 10.0.0.5, does not by itself let the server reach it: that also needs
--allow-private-ips, which in turn does not lift the allowlist.
{
"mcpServers": {
"fetch": {
"command": "uvx",
"args": ["mcp-server-fetch", "--allowed-hosts", "docs.python.org", "*.wikipedia.org"]
}
}
}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 - Timeout
The HTTP request for the page waits up to 30 seconds (30000 ms) by default: to connect, and then for each read of the response. It bounds each of those separately, not the whole download, so a large page that keeps arriving is not cut off. A request that times out fails with a tool error saying how long it waited.
The timeout can be set at three levels, the most specific winning:
The
fetchtool'stimeout_msargument, for one call (for example120000for a large download, or5000to fail fast).The argument
--timeout-ms=60000in theargslist in the configuration, for every call.The
FETCH_TIMEOUT_MSenvironment variable (for example"env": {"FETCH_TIMEOUT_MS": "60000"}in the configuration), for every call when--timeout-msis not given.
The server-wide value also applies to the fetch prompt, and is the default the tool advertises for timeout_ms.
Every level takes a whole number of milliseconds from 100 to 600000 (10 minutes); the server refuses to start with a
value outside that range, and the tool refuses such a timeout_ms. This is the HTTP request timeout only: the
robots.txt check before an autonomous fetch keeps its own 5-second timeout, and HTML extraction is not covered.
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.
Customization - HTML extraction
HTML is converted to Markdown with readabilipy. When Node.js 14
or newer is on the PATH, the server runs Mozilla's Readability.js (readabilipy's ExtractArticle.js) in a Node.js
subprocess; otherwise it uses readabilipy's pure-Python extractor, which keeps headings and text but drops link
targets. The subprocess runs off the server's event loop, so other requests are answered while it works, and under a
30 second timeout: a Node.js that hangs is killed, together with anything it started, and that page is extracted with
the pure-Python extractor instead. If Readability.js fails in any other way, the same fallback is used. Every reason
for a fallback is written to stderr (the server's log), never to stdout, which carries the protocol.
Readability.js's dependencies are installed with npm on first use, which reaches the npm registry. readabilipy
ships only the package.json for its JavaScript (@mozilla/readability, jsdom, minimist). The first time the
server extracts HTML with Node.js on the PATH and those packages missing, it runs npm install in readabilipy's
javascript directory, inside that tool call, so:
registry.npmjs.orgbelongs in the egress allowlist of a deployment that restricts outbound traffic, unless the packages are installed ahead of time (below) or Readability.js is turned off. Without it the install fails and the server uses the pure-Python extractor.The JavaScript that runs is resolved from readabilipy's unpinned version ranges when it is installed, so pinning
mcp-server-fetchdoes not pin it.The install runs at most once per server process, under a 120 second timeout. Its output goes to stderr. If it fails, or Node.js is missing or older than 14, the server uses the pure-Python extractor until it is restarted.
To install the packages ahead of time (in a container image, say), run npm install in readabilipy's javascript
directory from the Python environment the server runs in; the server then finds them and installs nothing:
cd "$(python -c "import os, readabilipy; print(os.path.join(os.path.dirname(readabilipy.__file__), 'javascript'))")"
npm install --no-audit --no-fundReadability.js discards hidden elements. Pages rendered progressively on the server often send a visible loading
shell, then the real content in a container hidden (display: none, visibility: hidden, hidden) until scripts
run in the browser. When a hidden element other than navigation or similar page furniture holds more text than
Readability.js extracted, the server unhides it and runs Readability.js again, keeping that result only if it has more
text. Other pages are extracted once, exactly as before.
To always use the pure-Python extractor, add the argument --no-readability-js to the args list in the
configuration. The server then never starts Node.js (or npm), whether or not it is installed, and never contacts the
npm registry.
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.
Readability.js works on Windows as it does elsewhere: the server finds Node.js and npm (npm.cmd) on the PATH, and
installs Readability.js's dependencies on first use as described in
Customization - HTML extraction.
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 (and, in tests/test_eras.py, through a Client as a 2026-07-28 and as a 2025-11-25 client), with HTTP mocked, so they need no network. The HTML extraction tests need Node.js and npm on PATH (the server uses Readability.js when Node is present and a pure-Python fallback when it is not), and the first run installs Readability.js's dependencies from the npm registry.
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 toolfetchBRead-onlyIdempotent
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. | |
| timeout_ms | No | How long to wait, in milliseconds, to connect to the server and for each read of its response before giving up. Raise it for a slow server or a large download; lower it to fail fast. | |
| 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?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description contributes the markdown-extraction default and the important note that prior no-internet guidance no longer applies, but says nothing about truncation, response size limits, redirects, or failure modes even though the schema exposes max_length and start_index for paging.
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 first sentence is tight and front-loaded, but the second paragraph is meta-commentary about the agent's previous instructions rather than tool behavior, and sits ahead of any return-value or limit information. It earns partial credit for correcting stale guidance but is not efficient.
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?
For a single-URL fetch with no output schema, the description should convey that the return is truncated markdown/HTML text and how to continue past truncation. It hints at markdown conversion but leaves return shape and paging behavior to the schema, and omits any error or timeout behavior.
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%, so every parameter including raw, max_length, start_index and timeout_ms is already documented with defaults and ranges; the description adds nothing parameter-specific beyond the markdown/HTML distinction. Baseline 3 applies when the schema does the heavy lifting.
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?
States a specific verb and resource ("Fetches a URL from the internet") and adds the meaningful behavioral detail that contents are converted to markdown. Slight ambiguity remains about when markdown versus raw HTML is returned, but the core purpose is unmistakable.
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 second paragraph implies when to use it (to get up-to-date information and tell the user), and usefully overrides any prior instruction to refuse internet requests. It never states exclusions, cost/latency tradeoffs, or when a different approach (e.g., asking the user) is preferable.
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
v2.3.0- Changed
fetch1 field changed- added
Input schema / properties / timeout_msAdded value: +{ + "default": 30000, + "description": "How long to wait, in milliseconds, to connect to the server and for each read of its response before giving up. Raise it for a slow server or a large download; lower it to fail fast.", + "maximum": 600000, + "minimum": 100, + "title": "Timeout Ms", + "type": "integer" +}
1 tool update
v2.0.0- Changed
fetch2 fields changed- removed
Input schema / descriptionRemoved value: -"Parameters for fetching a URL." - changed
Input schema / titlePrevious value: -"Fetch"New value: +"fetchArguments"
1 tool update
- Changed
fetch4 fields changed- removed
Input schema / properties / max_length / exclusiveMaximumRemoved value: -1000000 - removed
Input schema / properties / max_length / exclusiveMinimumRemoved value: -0 - added
Input schema / properties / max_length / maximumAdded value: +999999 - added
Input schema / properties / max_length / minimumAdded value: +1
1 tool update
v1.0.0- First observed
fetch
TDQS
Scored across 1 tool
There is only one tool, so there is no possibility of confusion with another operation. The tool's purpose (fetch a URL, optionally convert to markdown) is unambiguous.
The single name 'fetch' is a clear verb that directly describes the action, and there are no competing conventions to clash with it. Nothing inconsistent exists in the namespace.
The server's scope (retrieve web content) is genuinely served by a single tool, so one tool is defensible rather than bloated. It is still thinner than a typical 3-15 tool surface, leaving little room for specialized variants.
A fetch tool covers the core operation of an internet-access server, including raw and markdown output modes. Minor gaps exist around request customization (headers, methods, or batching multiple URLs) that an agent cannot work around.
Maintenance
Related MCP Connectors
MCP Server for Web2MD — convert URLs to Markdown from Claude Desktop, Cursor, etc.
Turn any web page URL or HTML into clean Markdown or plain text for an LLM to read.
Web scraping for AI agents. Converts URLs to clean, LLM-ready Markdown with anti-bot bypass.
Read any web page as clean Markdown for AI agents: fetch, search, metadata, links. SSRF-safe.
Related MCP Servers
AlicenseBqualityDmaintenanceThis server converts webpages into clean, structured Markdown optimized for language model consumption, removing unnecessary content and supporting JavaScript rendering.112MIT- AlicenseBqualityDmaintenanceA Model Context Protocol server that allows LLMs to retrieve and convert web content to markdown without robots.txt restrictions.12MIT
- AlicenseAqualityCmaintenanceAn MCP server that fetches web pages and extracts clean, AI-friendly Markdown content using Mozilla Readability. It provides secure web access for LLMs with built-in SSRF protection and automated content cleaning for improved context retrieval and summarization.1515 npmMIT
- AlicenseNot gradedqualityBmaintenanceConverts web pages to Markdown for MCP clients like Claude, with support for single and batch reads, caching, fallback rendering, and SSRF protection.22 npmMIT