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Fetch MCP Server

by XInTheDark
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

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-server-fetch.

Using PIP

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

pip install mcp-server-fetch

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

python -m mcp_server_fetch

Related MCP server: Fetch MCP Server

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...

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.

{
  "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 - 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-server-fetch

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-server-fetch

Contributing

We encourage contributions to help expand and improve mcp-server-fetch. 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-server-fetch even more powerful and useful.

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 tool
fetchC

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesURL to fetch
max_lengthNoMaximum number of characters to return.
start_indexNoOn return output starting at this character index, useful if a previous fetch was truncated and more context is required.
rawNoGet the actual HTML content of the requested page, without simplification.

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions internet access capability and markdown extraction, but fails to describe important behavioral traits: rate limits, authentication requirements, error handling, timeout behavior, or what happens when max_length is exceeded. The description doesn't contradict annotations (since none exist), but provides insufficient behavioral context 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.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is poorly structured and contains unnecessary information. The first sentence is clear, but the second paragraph about historical internet access limitations is irrelevant to the tool's current functionality and doesn't help the agent use the tool correctly. This wasted space reduces the description's effectiveness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema that performs external network operations, the description is incomplete. It doesn't explain what the tool returns (beyond mentioning markdown extraction), doesn't describe error conditions, and provides minimal behavioral context. The historical internet access paragraph adds no value to the agent's understanding of how to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all four parameters. The description mentions 'optionally extracts its contents as markdown' which hints at the 'raw' parameter's purpose, but doesn't add meaningful semantic context beyond what the schema provides. This meets the baseline expectation when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: fetching URLs from the internet and optionally extracting contents as markdown. It specifies the verb ('fetches') and resource ('URL from the internet'), though it doesn't need to distinguish from siblings since none exist. The second paragraph adds context about internet access but doesn't enhance the core purpose statement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions that internet access was previously unavailable but now is, which is historical context rather than usage guidance. There are no explicit instructions about when this tool is appropriate or when other approaches might be better.

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. 1 tool updatev1.0.0
    • First observedfetch
Install Server
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TDQS

C2.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'fetch' has a clearly distinct and singular purpose.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'fetch' is clear and follows a simple verb pattern.

Tool Count2/5

One tool is too few for a server named 'Fetch MCP Server' that implies broader internet access capabilities. While the tool is useful, the scope feels thin, lacking complementary tools like search, filter, or validate URLs.

Completeness2/5

The tool surface is severely incomplete for internet access. It only fetches URLs and extracts markdown, missing essential operations like handling different content types, error handling for failed requests, or advanced features like caching or rate limiting.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

Related MCP Servers

  • Fetch MCP Server

    aglolz
    A
    license
    B
    quality
    D
    maintenance
    Enables LLMs to retrieve and process web content by fetching URLs and converting HTML to markdown format. Supports chunked reading of large pages and can access both public websites and local networks.
    1
    MIT

  • Fetch MCP Server

    AkM-2018
    A
    license
    A
    quality
    D
    maintenance
    Enables LLMs to fetch and process web content by converting HTML into markdown for easier consumption. It supports chunked reading via pagination and provides configuration options for robots.txt compliance and proxy usage.
    1
    MIT

  • fetch

    RMRanjit
    A
    license
    Not graded
    quality
    D
    maintenance
    Fetches web pages and converts them to markdown for LLM consumption, supporting chunked reading and raw content extraction.
    MIT

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