Skip to main content

A Model Context Protocol server providing tools to fetch and convert web content for usage by LLMs

Project description

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.

[!CAUTION] 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.

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 fetch
    • max_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-fetch-sample.

Using PIP

Alternatively you can install mcp-fetch-sample via pip:

pip install mcp-fetch-sample

After installation, you can run it as a script using:

python -m mcp_server_fetch

Configuration

Configure for Claude.app

Add to your Claude settings:

Using uvx
{
  "mcpServers": {
    "fetch": {
      "command": "uvx",
      "args": ["mcp-fetch-sample"]
    }
  }
}
Using docker
{
  "mcpServers": {
    "fetch": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "mcp/fetch"]
    }
  }
}
Using pip installation
{
  "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...

Install with UV in VS Code Install with UV in VS Code Insiders

Install with Docker in VS Code Install with Docker in VS Code Insiders

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 mcp key is needed when using the mcp.json file.

Using uvx
{
  "mcp": {
    "servers": {
      "fetch": {
        "command": "uvx",
        "args": ["mcp-fetch-sample"]
      }
    }
  }
}
Using Docker
{
  "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 - 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.

Debugging

You can use the MCP inspector to debug the server. For uvx installations:

npx @modelcontextprotocol/inspector uvx mcp-fetch-sample

Or 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-fetch-sample

Contributing

We encourage contributions to help expand and improve mcp-fetch-sample. Whether you want to add new tools, enhance existing functionality, or improve documentation, your input is valuable.

For examples of other MCP servers and implementation patterns, see: https://github.com/modelcontextprotocol/servers

Pull requests are welcome! Feel free to contribute new ideas, bug fixes, or enhancements to make mcp-fetch-sample even more powerful and useful.

License

mcp-fetch-sample 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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_fetch_sample-0.6.4.tar.gz (50.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_fetch_sample-0.6.4-py3-none-any.whl (12.1 kB view details)

Uploaded Python 3

File details

Details for the file mcp_fetch_sample-0.6.4.tar.gz.

File metadata

  • Download URL: mcp_fetch_sample-0.6.4.tar.gz
  • Upload date:
  • Size: 50.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mcp_fetch_sample-0.6.4.tar.gz
Algorithm Hash digest
SHA256 3a33f0faf42431fc4458892f4a7e9f030148adb7a0c535c785bfe4f66607f2e3
MD5 22325ca8517859e0ce9acacf577de601
BLAKE2b-256 0cc58e46909d05c5c454feba69dd397bfc8f3c92230db105ab97adfff255373a

See more details on using hashes here.

Provenance

The following attestation bundles were made for mcp_fetch_sample-0.6.4.tar.gz:

Publisher: publish-to-pypi.yml on karlorz/fetch

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mcp_fetch_sample-0.6.4-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_fetch_sample-0.6.4-py3-none-any.whl
Algorithm Hash digest
SHA256 6f76965d6284aae3b06818d1fa0fb327c331f32656a58f5e655b7f551a2393c4
MD5 94b659bc3617cc1ab6005d847a75deb9
BLAKE2b-256 eb2f1c74252fcb16ab40cfc89ae303a77e74ba055271f0ad9930fc1773884647

See more details on using hashes here.

Provenance

The following attestation bundles were made for mcp_fetch_sample-0.6.4-py3-none-any.whl:

Publisher: publish-to-pypi.yml on karlorz/fetch

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page