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adiletD

Supabase MCP Server

by adiletD

query_feature_suggestions

Retrieve feature suggestions from a Supabase database to help AI tools access and display feature request data for analysis and implementation planning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of records to return

Implementation Reference

  • The handler function for the 'query_feature_suggestions' tool. It queries the 'feature_suggestions' table from Supabase, handles errors, logs data, and returns the results as JSON string in the response content.
    async ({ limit = 100 }) => {
      const table_name = "feature_suggestions";
      try {
        logger.log(`Querying feature_suggestions table with limit: ${limit}`);
        
        const { data, error } = await supabase
          .from(table_name)
          .select('*')
          .limit(limit);
        
        if (error) {
          logger.error(`Error querying feature_suggestions table:`, error);
          return {
            content: [{ 
              type: "text", 
              text: `Error querying feature_suggestions table: ${error.message}` 
            }]
          };
        }
        
        // Log the raw data for debugging
        logger.log(`Raw data from feature_suggestions: ${JSON.stringify(data)}`);
        
        // Ensure data is properly formatted
        const formattedData = Array.isArray(data) ? data : [];
        logger.log(`Successfully retrieved ${formattedData.length} records from feature_suggestions`);
        
        return {
          content: [{ 
            type: "text", 
            text: JSON.stringify(formattedData, null, 2) 
          }]
        };
      } catch (error) {
        logger.error(`Error in query_feature_suggestions tool for feature_suggestions table:`, error);
        return {
          content: [{ 
            type: "text", 
            text: `Error: ${error instanceof Error ? error.message : String(error)}` 
          }]
        };
      }
    }
  • Input schema for the 'query_feature_suggestions' tool, defining an optional 'limit' parameter as a number.
    {
      limit: z.number().optional().describe("Maximum number of records to return")
    },
  • mcp-server.ts:61-109 (registration)
    Registration of the 'query_feature_suggestions' tool using server.tool(name, inputSchema, handler), including the tool name, schema, and handler function.
    server.tool(
      "query_feature_suggestions",
      {
        limit: z.number().optional().describe("Maximum number of records to return")
      },
      async ({ limit = 100 }) => {
        const table_name = "feature_suggestions";
        try {
          logger.log(`Querying feature_suggestions table with limit: ${limit}`);
          
          const { data, error } = await supabase
            .from(table_name)
            .select('*')
            .limit(limit);
          
          if (error) {
            logger.error(`Error querying feature_suggestions table:`, error);
            return {
              content: [{ 
                type: "text", 
                text: `Error querying feature_suggestions table: ${error.message}` 
              }]
            };
          }
          
          // Log the raw data for debugging
          logger.log(`Raw data from feature_suggestions: ${JSON.stringify(data)}`);
          
          // Ensure data is properly formatted
          const formattedData = Array.isArray(data) ? data : [];
          logger.log(`Successfully retrieved ${formattedData.length} records from feature_suggestions`);
          
          return {
            content: [{ 
              type: "text", 
              text: JSON.stringify(formattedData, null, 2) 
            }]
          };
        } catch (error) {
          logger.error(`Error in query_feature_suggestions tool for feature_suggestions table:`, error);
          return {
            content: [{ 
              type: "text", 
              text: `Error: ${error instanceof Error ? error.message : String(error)}` 
            }]
          };
        }
      }
    );
Behavior1/5

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

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

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

Parameters1/5

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

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no 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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