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max-paulus

gong-mcp

by max-paulus

getv2users

Retrieve user listings from Gong in paginated format. This tool fetches users in 100-row pages using cursor-based navigation for efficient data access.

Instructions

List Gong users (100-row pages)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNo

Implementation Reference

  • src/index.ts:90-99 (registration)
    Registration of the 'getv2users' tool in the toolDefinitionMap. Includes name, description, input schema for optional 'cursor' parameter, GET method, path '/v2/users', query parameter mapping, and basicAuth security.
    ["getv2users", {
      name: "getv2users",
      description: `List Gong users (100-row pages)`,
      inputSchema: {"type":"object","properties":{"cursor":{"type":"string"}}},
      method: "get",
      pathTemplate: "/v2/users",
      executionParameters: [{"name":"cursor","in":"query"}],
      requestBodyContentType: undefined,
      securityRequirements: [{"basicAuth":[]}]
    }],
  • Input schema for 'getv2users' tool: an object with optional 'cursor' string property.
    inputSchema: {"type":"object","properties":{"cursor":{"type":"string"}}},
  • Generic handler function that implements the logic for all tools, including 'getv2users'. Parses input schema to Zod for validation, constructs API URL (https://api.gong.io/v2/users?cursor=...), authenticates with Basic Auth, calls Gong API via axios, and returns the JSON response.
    async function executeApiTool(
        toolName: string,
        definition: McpToolDefinition,
        toolArgs: JsonObject,
        allSecuritySchemes: Record<string, any>
    ): Promise<CallToolResult> {
        try {
            // Validate input arguments using Zod
            const zodSchema = getZodSchemaFromJsonSchema(definition.inputSchema, toolName);
            const validatedArgs = zodSchema.parse(toolArgs);
    
            // Build the request URL
            let url = API_BASE_URL + definition.pathTemplate;
            
            // Replace path parameters
            for (const param of definition.executionParameters) {
                if (param.in === 'path') {
                    const value = validatedArgs[param.name];
                    if (value !== undefined) {
                        url = url.replace(`{${param.name}}`, encodeURIComponent(value));
                    }
                }
            }
    
            // Build query parameters
            const queryParams: Record<string, string> = {};
            for (const param of definition.executionParameters) {
                if (param.in === 'query') {
                    const value = validatedArgs[param.name];
                    if (value !== undefined) {
                        queryParams[param.name] = value;
                    }
                }
            }
            
            if (Object.keys(queryParams).length > 0) {
                url += '?' + new URLSearchParams(queryParams).toString();
            }
    
            // Debug logging (safe)
            console.error('Debug - Making API request to:', url);
            
            // Get credentials from environment
            const accessKey = process.env.GONG_ACCESS_KEY || '';
            const secret = process.env.GONG_SECRET || '';
            
            if (!accessKey || !secret) {
                throw new Error('Missing Gong credentials in environment');
            }
            
            // Create authorization header
            const authHeader = `Basic ${Buffer.from(`${accessKey}:${secret}`).toString('base64')}`;
            
            // Build request config
            const config: AxiosRequestConfig = {
                method: definition.method,
                url,
                headers: {
                    'Accept': 'application/json',
                    'Authorization': authHeader
                }
            };
    
            // Add request body if needed
            if (definition.requestBodyContentType) {
                config.headers!['Content-Type'] = definition.requestBodyContentType;
                if (validatedArgs.requestBody) {
                    config.data = validatedArgs.requestBody;
                }
            }
    
            // Make the request
            const response = await axios(config);
            
            return {
                content: [
                    {
                        type: 'text',
                        text: JSON.stringify(response.data, null, 2)
                    }
                ]
            };
    
        } catch (error: any) {
            if (error instanceof ZodError) {
                return {
                    content: [{
                        type: 'text',
                        text: `Validation error: ${error.message}`
                    }]
                };
            }
            
            if (axios.isAxiosError(error)) {
                return {
                    content: [{
                        type: 'text',
                        text: formatApiError(error)
                    }]
                };
            }
    
            return {
                content: [{
                    type: 'text',
                    text: `Unexpected error: ${error.message}`
                }]
            };
        }
    }
  • MCP server request handler for tool calls. Retrieves tool definition by name ('getv2users') and dispatches to executeApiTool.
    server.setRequestHandler(CallToolRequestSchema, async (request: CallToolRequest): Promise<CallToolResult> => {
      const { name: toolName, arguments: toolArgs } = request.params;
      const toolDefinition = toolDefinitionMap.get(toolName);
      if (!toolDefinition) {
        console.error(`Error: Unknown tool requested: ${toolName}`);
        return { content: [{ type: "text", text: `Error: Unknown tool requested: ${toolName}` }] };
      }
      return await executeApiTool(toolName, toolDefinition, toolArgs ?? {}, securitySchemes);
    });
  • Helper function to convert the tool's JSON inputSchema to a Zod schema for runtime validation in the handler.
    function getZodSchemaFromJsonSchema(jsonSchema: any, toolName: string): z.ZodTypeAny {
        if (typeof jsonSchema !== 'object' || jsonSchema === null) { 
            return z.object({}).passthrough(); 
        }
        try {
            const zodSchemaString = jsonSchemaToZod(jsonSchema);
            const zodSchema = eval(zodSchemaString);
            if (typeof zodSchema?.parse !== 'function') { 
                throw new Error('Eval did not produce a valid Zod schema.'); 
            }
            return zodSchema as z.ZodTypeAny;
        } catch (err: any) {
            console.error(`Failed to generate/evaluate Zod schema for '${toolName}':`, err);
            return z.object({}).passthrough();
        }
    }
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the pagination behavior ('100-row pages'), which is a key trait beyond the input schema. However, it doesn't mention other important behaviors like authentication requirements, rate limits, error handling, or what data fields are returned. The description adds some value but leaves significant gaps.

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 just one short phrase ('List Gong users (100-row pages)'). It's front-loaded with the core purpose and includes essential behavioral detail (pagination) in parentheses. Every word earns its place with zero 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 no annotations, no output schema, and low schema coverage (0%), the description is incomplete. It covers the basic purpose and pagination but misses critical context: parameter meaning, authentication, rate limits, return format, and error handling. For a tool with one undocumented parameter and no structured metadata, this leaves too many gaps for effective use.

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 ('cursor') with 0% description coverage, so the schema provides no semantic information. The description doesn't mention the 'cursor' parameter at all, failing to compensate for the schema's lack of documentation. It only implies pagination indirectly through '100-row pages', but doesn't explain how the cursor relates to this.

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 verb 'List' and the resource 'Gong users', making the purpose specific and understandable. However, it doesn't differentiate this tool from potential sibling user-related tools (none are listed among siblings, but the description doesn't address this explicitly).

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 pagination ('100-row pages') but doesn't explain when to use this paginated list versus other user-related operations or how it fits into workflows. No exclusions or prerequisites are stated.

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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