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MCP Web Research Server

by chuanmingliu
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MCP Web Research Server

A Model Context Protocol (MCP) server for web research.

Bring real-time info into Claude and easily research any topic.

Features

  • Google search integration

  • Webpage content extraction

  • Research session tracking (list of visited pages, search queries, etc.)

  • Screenshot capture

Related MCP server: MCP Web Research Server

Prerequisites

Installation

First, ensure you've downloaded and installed the Claude Desktop app and you have npm installed.

Next, add this entry to your claude_desktop_config.json (on Mac, found at ~/Library/Application\ Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "webresearch": {
      "command": "npx",
      "args": ["-y", "@mzxrai/mcp-webresearch@latest"]
    }
  }
}

This config allows Claude Desktop to automatically start the web research MCP server when needed.

Usage

Simply start a chat with Claude and send a prompt that would benefit from web research. If you'd like a prebuilt prompt customized for deeper web research, you can use the agentic-research prompt that we provide through this package. Access that prompt in Claude Desktop by clicking the Paperclip icon in the chat input and then selecting Choose an integration → webresearch → agentic-research.

Tools

  1. search_google

    • Performs Google searches and extracts results

    • Arguments: { query: string }

  2. visit_page

    • Visits a webpage and extracts its content

    • Arguments: { url: string, takeScreenshot?: boolean }

  3. take_screenshot

    • Takes a screenshot of the current page

    • No arguments required

Prompts

agentic-research

A guided research prompt that helps Claude conduct thorough web research. The prompt instructs Claude to:

  • Start with broad searches to understand the topic landscape

  • Prioritize high-quality, authoritative sources

  • Iteratively refine the research direction based on findings

  • Keep you informed and let you guide the research interactively

  • Always cite sources with URLs

Resources

We expose two things as MCP resources: (1) captured webpage screenshots, and (2) the research session.

Screenshots

When you take a screenshot, it's saved as an MCP resource. You can access captured screenshots in Claude Desktop via the Paperclip icon.

Research Session

The server maintains a research session that includes:

  • Search queries

  • Visited pages

  • Extracted content

  • Screenshots

  • Timestamps

Suggestions

For the best results, if you choose not to use the agentic-research prompt when doing your research, it may be helpful to suggest high-quality sources for Claude to use when researching general topics. For example, you could prompt news today from reuters or AP instead of news today.

Problems

This is very much pre-alpha code. And it is also AIGC, so expect bugs.

If you run into issues, it may be helpful to check Claude Desktop's MCP logs:

tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

Development

# Install dependencies
pnpm install

# Build the project
pnpm build

# Watch for changes
pnpm watch

# Run in development mode
pnpm dev

Requirements

  • Node.js >= 18

  • Playwright (automatically installed as a dependency)

Verified Platforms

  • macOS

  • Linux

License

MIT

Author

mzxrai

Available Tools

3 tools
search_googleC

Search Google for a query

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query

TDQS

C2.7/5.0
Behavior1/5

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 but offers none. It doesn't mention whether this is a read-only operation, if it requires authentication, what rate limits might apply, what format results come in, or any other behavioral characteristics beyond the basic action.

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 extremely concise at just 5 words, front-loading the essential information with zero wasted words. Every word earns its place in communicating the core functionality.

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 search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of results to expect, whether there are limitations on queries, or any other contextual information needed for effective use beyond the bare minimum.

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 schema description coverage is 100%, with the single parameter 'query' already documented in the schema. The description adds no additional semantic context about the parameter beyond what's in the schema, so it meets the baseline for high schema coverage.

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 'Search Google for a query' clearly states the action (search) and target resource (Google), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'take_screenshot' or 'visit_page', but those perform completely different functions, so differentiation isn't critical here.

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. While the sibling tools are functionally different, there's no mention of when to prefer this search tool over other potential search methods or when it might be inappropriate to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

take_screenshotB

Take a screenshot of the current page

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits. It doesn't mention what happens after the screenshot (e.g., saved location, format, permissions needed, or error conditions), which is critical for a tool with potential side effects.

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 a single, efficient sentence that front-loads the core action without any wasted words. It's appropriately sized for a simple tool with no parameters, making it easy for an agent to parse quickly.

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?

Given the tool's complexity (simple action but with behavioral implications) and lack of annotations/output schema, the description is incomplete. It doesn't address what the tool returns (e.g., file path, base64 data) or error handling, leaving significant gaps for agent invocation.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description doesn't need to add parameter details, and it correctly implies no inputs are required for this operation.

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 action ('take') and target resource ('screenshot of the current page'), making the purpose immediately understandable. However, it doesn't differentiate from potential siblings like 'capture_region' or 'record_screen', which would require explicit comparison to achieve a perfect score.

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 like 'search_google' or 'visit_page'. It lacks context about prerequisites (e.g., needing an active page) or exclusions (e.g., not working on certain page types), leaving the agent with minimal usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

visit_pageC

Visit a webpage and extract its content

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesURL to visit
takeScreenshotNoWhether to take a screenshot

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full burden but provides minimal behavioral context. It mentions 'extract its content' but doesn't specify what content (e.g., HTML, text, metadata), how extraction works (e.g., parsing, rendering), or any constraints (e.g., rate limits, authentication needs, timeouts). The description doesn't contradict annotations (none provided), but lacks critical operational details.

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 a single, efficient sentence with zero waste. It's front-loaded with the core action and outcome, making it easy to parse. Every word earns its place, and there's no redundant or verbose phrasing.

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?

Given the tool's complexity (web interaction with potential side effects like network calls), lack of annotations, and no output schema, the description is incomplete. It doesn't cover return values, error handling, performance characteristics, or dependencies. For a tool that likely involves external resources and mutation-like behavior (extracting content), more context is needed.

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 documents both parameters ('url' and 'takeScreenshot') adequately. The description adds no additional parameter semantics beyond what's in the schema (e.g., no format details for URL, no explanation of how screenshot integrates with content extraction). Baseline 3 is appropriate as the schema does the heavy lifting.

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 action ('visit') and resource ('webpage'), and specifies the outcome ('extract its content'). It distinguishes from 'search_google' (which searches) and 'take_screenshot' (which only captures images), but doesn't explicitly differentiate from siblings beyond implied scope. The purpose is specific and actionable.

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?

No explicit guidance on when to use this tool versus alternatives is provided. The description implies usage for content extraction from a known URL, but doesn't mention when to prefer 'search_google' (for finding URLs) or 'take_screenshot' (for visual capture only). There's no context on prerequisites, limitations, or exclusions.

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. 3 tool updates
    • First observedsearch_google
    • First observedtake_screenshot
    • First observedvisit_page
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TDQS

B3.2/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: search_google finds web pages, visit_page loads and extracts content from a specific URL, and take_screenshot captures the current page. An agent can easily distinguish between these functions without confusion.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (search_google, take_screenshot, visit_page), making them predictable and readable. There are no deviations or mixed conventions in the naming style.

Tool Count3/5

With only 3 tools, the set feels thin for a 'Web Research Server' as it lacks operations like saving results, navigating pages, or handling multiple tabs. While the tools cover basic web interactions, the count is borderline low for comprehensive research tasks.

Completeness3/5

The tools provide core functions (search, visit, screenshot) but leave notable gaps for a research server, such as no ability to interact with page elements, manage sessions, or export data. Agents can work around this for simple tasks, but advanced research workflows will be limited.

Maintenance

ActivityInactive
ResponsivenessNo issues

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