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questflowai

Aster Finance MCP Server

by questflowai

getCommissionRate

Retrieve commission rates for cryptocurrency trading on Aster Finance. Use this tool to check current commission percentages for specific trading pairs before executing trades.

Instructions

Get user's commission rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes

Implementation Reference

  • src/index.ts:524-534 (registration)
    Registration of the 'getCommissionRate' tool, including its description and input schema requiring a 'symbol'.
    {
      name: 'getCommissionRate',
      description: "Get user's commission rate.",
      inputSchema: {
        type: 'object',
        properties: {
          symbol: { type: 'string' },
        },
        required: ['symbol'],
      },
    },
  • Handler implementation for 'getCommissionRate' tool. Makes a signed GET request to the Aster API endpoint '/fapi/v1/commissionRate' with the provided arguments.
    case 'getCommissionRate':
        return makeRequest('GET', '/fapi/v1/commissionRate', args, true);
  • Input schema for 'getCommissionRate' tool, defining the required 'symbol' parameter.
    inputSchema: {
      type: 'object',
      properties: {
        symbol: { type: 'string' },
      },
      required: ['symbol'],
  • Shared 'makeRequest' helper function used by the handler to perform signed API requests to AsterDex.
    const makeRequest = async (method: 'GET' | 'POST' | 'DELETE', path: string, params: any, isSigned = false) => {
      try {
        let config: any = {
          method,
          url: path,
        };
    
        if (isSigned) {
          if (!API_KEY || !API_SECRET) {
            throw new McpError(ErrorCode.InvalidRequest, 'API_KEY and API_SECRET must be configured.');
          }
          params.timestamp = Date.now();
          const queryString = new URLSearchParams(params).toString();
          const signature = crypto.createHmac('sha256', API_SECRET).update(queryString).digest('hex');
          params.signature = signature;
          
          config.headers = { 'X-MBX-APIKEY': API_KEY };
        }
        
        if (method === 'GET' || method === 'DELETE') {
          config.params = params;
        } else { // POST
          config.data = new URLSearchParams(params).toString();
          config.headers = { ...config.headers, 'Content-Type': 'application/x-www-form-urlencoded' };
        }
    
        const response = await this.axiosInstance.request(config);
        return { content: [{ type: 'text', text: JSON.stringify(response.data, null, 2) }] };
      } catch (error) {
        if (axios.isAxiosError(error)) {
          throw new McpError(
            ErrorCode.InternalError,
            `Aster API error: ${error.response?.data?.msg || error.message}`
          );
        }
        throw error;
      }
    };
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 states a read operation ('Get'), implying it's likely safe and non-destructive, but doesn't cover aspects like authentication needs, rate limits, error conditions, or what the return format might be. The description is minimal and lacks behavioral context 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.

Conciseness4/5

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

The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it's front-loaded but under-specified, as it could benefit from more detail without sacrificing brevity. Every word earns its place, but the overall content is sparse.

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 (a read operation with 1 parameter), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't provide enough context for an agent to reliably invoke the tool, such as parameter semantics, return values, or behavioral traits. More detail is needed for adequate completeness.

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

Parameters2/5

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

The input schema has 1 parameter with 0% description coverage, and the description doesn't add any meaning beyond what the schema provides. It doesn't explain what 'symbol' represents (e.g., a trading pair, user identifier, or asset), its format, or how it relates to fetching the commission rate. With low schema coverage, the description fails to compensate.

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

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get user's commission rate' clearly states the action (get) and resource (commission rate), but it's vague about what 'user' refers to (e.g., a specific account or symbol) and doesn't distinguish from siblings like 'getAccountInfo' or 'getBalance' that might also retrieve user-related data. It avoids tautology by not just restating the name.

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 guidance is provided on when to use this tool versus alternatives. Sibling tools like 'getAccountInfo' or 'getBalance' might overlap in retrieving user data, but the description doesn't specify if this is for commission-specific queries or in what context it's preferred. Usage is implied only by the name and description.

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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