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MCP Web Tools

by SayreBlades
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Python
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MCP Web Tools

A Model Context Protocol (MCP) server that provides web search and fetch capabilities for AI assistants like Claude Code.

This is useful when you want your code-generation tool to make web requests directly from your machine, rather than having those requests proxied through an external server you don't control. The MCP server runs locally on your host, so all web requests originate from your own network.

Features

  • web_search - Search the web using DuckDuckGo

    • Returns formatted results with titles, URLs, and snippets

    • Configurable result count and region

  • web_fetch - Fetch and extract content from web pages

    • Automatic HTML-to-text conversion (removes scripts, styles, navigation)

    • JSON response formatting

    • Configurable timeout

Related MCP server: DuckDuckGo MCP Server

Requirements

  • Python 3.13+

  • uv

Installation

Quick Install (Recommended)

# Clone the repository
git clone <repo-url>
cd mcp-web-tools

# Install globally and configure Claude Code
make install

This will:

  1. Install mcp-web-tools as a global executable via uv tool install

  2. Register the MCP server with Claude Code using claude mcp add

  3. The executable will be available at ~/.local/bin/mcp-web-tools

Restart Claude Code after installation.

Manual Installation

# Install dependencies
uv sync

# Run directly from project
uv run mcp-web-tools

Makefile Targets

Target

Description

make install

Install globally and configure Claude Code

make uninstall

Remove the global installation

make test

Run tests with pytest

make clean

Remove build artifacts

Claude Code Configuration

After running make install, you can verify the registration:

claude mcp list

The tools will be available in Claude Code as:

  • mcp__web-tools__web_search

  • mcp__web-tools__web_fetch

Manual Registration

If you prefer to register manually:

# User-wide (available in all projects)
claude mcp add --scope user web-tools mcp-web-tools

# Project-local (only current project)
claude mcp add --scope project web-tools mcp-web-tools

Alternative: Run from Project Directory

For development, you can register to run directly from the source:

claude mcp add --scope project web-tools uv run --directory /path/to/mcp-web-tools mcp-web-tools

Tool Reference

web_search

Search the web using DuckDuckGo.

Parameters:

Parameter

Type

Required

Default

Description

query

string

Yes

-

The search query

max_results

integer

No

10

Maximum number of results

region

string

No

"wt-wt"

Region for results (e.g., "us-en", "uk-en")

Example response:

Search results for: python mcp server

1. Building MCP Servers in Python
   URL: https://example.com/article
   Learn how to build Model Context Protocol servers...

2. MCP Documentation
   URL: https://modelcontextprotocol.io/docs
   Official documentation for the Model Context Protocol...

web_fetch

Fetch the content of a web page.

Parameters:

Parameter

Type

Required

Default

Description

url

string

Yes

-

The URL to fetch

timeout

integer

No

30

Request timeout in seconds

Example response:

Content from https://example.com/article:

Building MCP Servers
This guide covers the basics of creating an MCP server...

Development

Running Tests

make test

# Or directly
uv run pytest -v

Project Structure

mcp-web-tools/
  src/
    mcp_web_tools/
      __init__.py       # Package metadata
      server.py         # MCP server implementation
      tools.py          # Tool implementations (search, fetch)
  tests/
    test_tools.py       # Unit tests
  pyproject.toml        # Project configuration
  Makefile              # Install/uninstall automation

Dependencies

  • mcp - Model Context Protocol SDK

  • ddgs - DuckDuckGo Search API

  • httpx - Async HTTP client

  • lxml - HTML parsing (optional; falls back to regex-based extraction if not installed)

License

MIT

Available Tools

2 tools
web_fetchB

Fetch the content of a web page. Returns the raw text content of the page, suitable for reading articles and documentation.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL to fetch
timeoutNoRequest timeout in seconds (default: 30)

TDQS

B3.3/5.0
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 the tool returns 'raw text content' and hints at use cases, but fails to disclose critical traits like error handling (e.g., for invalid URLs), authentication needs, rate limits, or performance considerations. This leaves significant gaps for a tool that interacts with external web resources.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is appropriately sized and front-loaded, consisting of two concise sentences that directly state the tool's function and its return value. Every sentence earns its place by providing essential information without redundancy, making it efficient and well-structured.

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

Completeness3/5

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

Given the tool's moderate complexity (fetching web content) and the absence of annotations and output schema, the description is partially complete. It covers the basic purpose and return type but lacks details on behavioral aspects, error handling, and output structure. This makes it adequate as a minimum viable description but with clear gaps in context.

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?

The input schema has 100% description coverage, clearly documenting both parameters ('url' and 'timeout'). The description adds no additional meaning beyond the schema, as it doesn't elaborate on parameter usage or constraints. According to the rules, with high schema coverage (>80%), the baseline is 3, which applies here since the description doesn't compensate with extra insights.

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 with a specific verb ('fetch') and resource ('content of a web page'), and distinguishes it from sibling 'web_search' by focusing on retrieving raw text from a given URL rather than searching. However, it doesn't explicitly differentiate from potential siblings like 'web_scrape' or 'web_metadata', keeping it at 4 instead of 5.

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

Usage Guidelines3/5

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

The description implies usage by stating it's 'suitable for reading articles and documentation,' suggesting contexts like content extraction. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'web_search' for broader queries) or any exclusions (e.g., not for dynamic pages), leaving usage somewhat inferred rather than clearly defined.

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. 2 tool updatesv0.1.0
    • First observedweb_fetch
    • First observedweb_search
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TDQS

A3.5/5.0
Disambiguation5/5

The two tools have clearly distinct purposes: web_fetch retrieves the content of a specific URL, while web_search queries a search engine for results. There is no overlap in functionality, making it easy for an agent to choose the correct tool based on the task.

Naming Consistency5/5

Both tools follow a consistent 'web_' prefix and snake_case naming pattern (web_fetch and web_search). This predictable structure enhances readability and usability for agents.

Tool Count2/5

With only 2 tools, the server feels thin for a 'Web Tools' domain. While fetch and search are core operations, the scope suggests potential for more functionality (e.g., parsing, navigation, or analytics), making the toolset appear incomplete.

Completeness3/5

The tools cover basic web interaction (fetching content and searching), but there are notable gaps. For a web tools server, missing operations like navigating links, extracting specific data, or handling web forms limit its utility for complex agent workflows.

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

  • DuckDuckGo MCP Server

    988664li-star
    A
    license
    B
    quality
    D
    maintenance
    Enables web search through DuckDuckGo and webpage content fetching with intelligent text extraction. Features built-in rate limiting and LLM-optimized result formatting for seamless integration with language models.
    2
    MIT

  • mcp-web

    TsFreddie
    A
    license
    Not graded
    quality
    F
    maintenance
    Enables AI agents to search DuckDuckGo and fetch web content with human-assisted CAPTCHA handling, designed for local use where humans can intervene when bot detection occurs.
    7
    MIT

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