Skip to main content
Glama
Nicolas-One

API Request MCP Server

by Nicolas-One
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

58%
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 with other tools, making disambiguation perfect. The tool has a clear and distinct purpose of sending API requests, so an agent cannot misselect between non-existent alternatives.

    Naming Consistency5/5

    The single tool name 'send_api_request' follows a consistent verb_noun pattern, and with no other tools to compare, there is no inconsistency. The naming is clear and predictable for the server's scope.

    Tool Count2/5

    A single tool is too few for a server named 'API Request MCP Server', which implies a broader scope for handling API interactions. This minimal set feels thin and incomplete for the apparent purpose, as it lacks operations like request configuration, error handling, or batch processing.

    Completeness2/5

    The tool surface is severely incomplete for an API request server. While 'send_api_request' covers the core action, there are obvious gaps such as no tools for managing request headers, authentication, retries, or parsing responses beyond JSON. This will likely cause agent failures in complex API workflows.

  • Average 2.9/5 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.

  • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden. It mentions returning JSON responses and supporting multiple protocols/proxies, but doesn't disclose critical behaviors like error handling, timeout settings, authentication requirements, rate limits, or what happens with non-JSON responses. For a general-purpose API tool, this is a significant gap.

    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 in Chinese that conveys the core functionality without waste. It's appropriately sized and front-loaded with the main purpose.

    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 complexity of a general API request tool with 5 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain return values, error conditions, or behavioral constraints. The agent lacks sufficient context to use this tool effectively beyond basic parameter filling.

    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 fully documents all 5 parameters. The description adds no additional parameter semantics beyond mentioning protocol and proxy support, which is already implied by the schema. Baseline 3 is appropriate when the schema does all the work.

    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: '发送API请求并返回JSON响应' (send API request and return JSON response). It specifies the action (send request) and outcome (return JSON response), and mentions support for multiple protocols and proxies. However, it doesn't differentiate from siblings since there are none, so it's not a 5.

    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 support for multiple protocols and proxies, but doesn't specify use cases, prerequisites, or limitations. With no siblings, this is less critical, but the description lacks any usage context.

    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

api-request-mcp-server MCP server

Copy to your README.md:

Score Badge

api-request-mcp-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/Nicolas-One/api-request-mcp-server'

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