Skip to main content
Glama
kwp-lab

MCP Fetch With Proxy

Server Quality Checklist

83%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools, making disambiguation perfect. The single tool has a clear and distinct purpose without any competing alternatives.

    Naming Consistency5/5

    The single tool name 'fetch' follows a simple verb pattern, and with only one tool, consistency is inherently perfect. There are no other tools to create naming conflicts or inconsistencies.

    Tool Count2/5

    A single tool is too few for most server purposes, as it limits functionality and flexibility. While it might suffice for basic fetching, it feels thin and under-scoped for a server named 'MCP Fetch With Proxy', which suggests broader capabilities.

    Completeness2/5

    The tool surface is severely incomplete; it only provides fetching and markdown extraction without supporting operations like configuration, error handling, or advanced proxy management. This leaves obvious gaps for a server with 'Proxy' in its name, such as setting or testing proxy settings.

  • Average 3.7/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • This repository includes a glama.json configuration file.

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • 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 content extraction and image URL inclusion, but doesn't cover important aspects like error handling (e.g., invalid URLs, network failures), rate limits, authentication needs, privacy implications, or what happens when maxLength is exceeded. The description is insufficient 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.

    Conciseness5/5

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

    The description is perfectly concise with two clear sentences that each add value. The first sentence establishes the primary function, and the second adds important behavioral detail about image handling. No wasted words or redundant information.

    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?

    For a tool with 4 parameters, no annotations, and no output schema, the description provides adequate basic functionality explanation but lacks sufficient detail about behavioral characteristics, error conditions, and output format. The absence of sibling tools reduces complexity, but the description should do more to compensate for the lack of structured metadata.

    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 description doesn't mention any parameters directly, but with 0% schema description coverage, it doesn't compensate for the lack of parameter documentation. However, the tool has 4 parameters with clear schema definitions (url, maxLength, startIndex, raw), and the description's focus on the core functionality provides some context. The baseline would be lower if the schema were less informative.

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

    Purpose5/5

    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 specific verbs ('retrieves', 'extracts') and resources ('URLs from the Internet', 'content as markdown'), and explicitly mentions handling of images. It distinguishes what the tool does without relying on the generic name 'fetch'.

    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 for retrieving and converting web content to markdown, but provides no explicit guidance on when to use this tool versus alternatives (though no sibling tools are listed). It lacks information about prerequisites, error conditions, or performance considerations.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-fetch MCP server

Copy to your README.md:

Score Badge

mcp-fetch MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/kwp-lab/mcp-fetch'

If you have feedback or need assistance with the MCP directory API, please join our Discord server