Skip to main content
Glama
x51xxx

@trishchuk/mcp-fetch-server

by x51xxx
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Local

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    With only a single tool, there is no possibility of confusion with other tools. The tool's purpose is clearly described and distinct by default.

    Naming Consistency3/5

    With only one tool, there is no pattern to judge. The name 'fetch' is simple and conventional, matching common HTTP client terminology, but the lack of a verb_noun convention is neutral.

    Tool Count2/5

    A single tool for an HTTP fetch server is too minimal. Most similar servers would include additional tools for managing headers, cookies, or caching, making this feel under-scoped for its stated purpose of scraping.

    Completeness2/5

    The server only provides a basic fetch tool with no support for managing sessions, handling redirects, managing cookies, or performing other common HTTP operations. This leaves significant gaps for any realistic scraping workflow.

  • Average 4.1/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 3 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • 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

  • Behavior4/5

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

    The description discloses the critical behavioral trait of browser fingerprint emulation (JA3/JA4, TLS, HTTP/2) to avoid detection. Without annotations, this provides transparency about why requests succeed. However, it does not mention whether the tool is read-only or has side effects, though HTTP fetch is inherently non-destructive to local state.

    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: two sentences that front-load the core purpose and differentiator, followed by usage guidance. Every sentence serves a purpose, and there is no redundancy or filler.

    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 has 16 parameters, no annotations, and no output schema, the description is somewhat incomplete. It does not explain what the tool returns (e.g., status code, headers, body format) or that the response is a standard HTTP response. While the schema covers some constraints like maxResponseBytes, the agent lacks clarity on what to expect after invocation.

    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 88%, so the input schema already documents most parameters. The description adds general context about the underlying library and fingerprinting motivation but does not provide additional details on individual parameters beyond what schema descriptions offer. The baseline of 3 is appropriate.

    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 identifies the tool as an HTTP fetch client with browser fingerprint emulation to bypass bot detection. It specifies the verb 'fetch', the resource (URLs), and the unique value proposition (curl-impersonate style). This distinguishes it from standard HTTP clients and makes its purpose immediately obvious.

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

    Usage Guidelines4/5

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

    The description explicitly states when to use the tool: 'against sites that block or challenge plain scrapers'. It contrasts with Node's default HTTP client, implying an alternative. However, it does not list explicit sibling tools or provide when-not-to-use guidance, such as for sites without bot detection.

    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-server MCP server

Copy to your README.md:

Score Badge

mcp-fetch-server 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/x51xxx/mcp-fetch-server'

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