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hanweg

Discord Raw API MCP Server

by hanweg
OverviewSchemaRelated ServersScoreDiscussions
Python
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 ambiguity or overlap between tools. The single tool 'discord_api' has a clearly distinct purpose that covers all Discord API interactions.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'discord_api' follows a clear and appropriate pattern for its function.

    Tool Count2/5

    A single tool for a Discord API server is too few for the apparent scope, as Discord's API typically involves multiple resources and operations (e.g., channels, messages, users). This forces all functionality through one generic tool, which is a mismatch for the domain's complexity.

    Completeness1/5

    The tool surface is severely incomplete for a Discord API server. While the single tool can execute any raw API command, there are no specific tools for common Discord operations (e.g., send_message, get_channel, list_members), leaving significant gaps that will likely cause agent failures due to lack of structured guidance.

  • Average 2.9/5 across 1 of 1 tools scored.

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

    • No issues in the last 6 months
    • No commit activity data available
    • 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.

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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 of behavioral disclosure. It states the tool 'Executes raw Discord API commands' which implies it performs operations, but it doesn't disclose critical traits like authentication requirements, rate limits, error handling, or whether it's read-only or destructive. The mention of 'Supports both REST API calls and application commands' adds some context but is insufficient for a mutation-capable tool.

    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 with two sentences that directly state the tool's function and scope. Every word earns its place, with no redundant or vague language. It is front-loaded and efficiently communicates the essential information without waste.

    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 raw API execution tool with no annotations and no output schema, the description is incomplete. It lacks details on authentication, rate limits, error responses, and the nature of operations (e.g., whether it can perform destructive actions). For a tool that handles both REST and application commands with potential mutations, more context is needed to guide safe and effective use.

    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 clear descriptions for all parameters (method, endpoint, payload). The description adds no additional meaning beyond what the schema provides—it doesn't explain parameter interactions, format specifics, or examples. Baseline 3 is appropriate since the schema does the heavy lifting, but 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: 'Execute raw Discord API commands' with the verb 'Execute' and resource 'Discord API commands'. It distinguishes between REST API calls and application commands, providing specific scope. However, without sibling tools, differentiation from alternatives is not applicable, preventing 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 or any prerequisites. It mentions support for 'both REST API calls and application commands', but this is part of the purpose statement rather than usage instructions. There are no explicit when/when-not scenarios or context for selection.

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

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