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gong-mcp

by max-paulus

getv2dataprivacydataforemailaddress

Retrieve GDPR-compliant data activities for an email address to support data privacy requests and compliance verification.

Instructions

Activities for an email address (GDPR helper)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailAddressYes
cursorNo

Implementation Reference

  • The generic handler function executeApiTool that implements the core logic for all tools, including getv2dataprivacydataforemailaddress. It validates input using Zod schema from inputSchema, builds the API URL (https://api.gong.io/v2/data-privacy/data-for-email-address with query params emailAddress and cursor), uses Basic Auth from GONG_ACCESS_KEY and GONG_SECRET env vars, makes axios GET request, 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}`
                }]
            };
        }
    }
  • src/index.ts:100-109 (registration)
    Registration of the tool in toolDefinitionMap, defining its metadata, input schema, API endpoint details (GET /v2/data-privacy/data-for-email-address), parameters (emailAddress and cursor as query params), and security (basicAuth). This entry enables the tool to be listed and dispatched.
    ["getv2dataprivacydataforemailaddress", {
      name: "getv2dataprivacydataforemailaddress",
      description: `Activities for an email address (GDPR helper)`,
      inputSchema: {"type":"object","properties":{"emailAddress":{"type":"string","format":"email"},"cursor":{"type":"string"}},"required":["emailAddress"]},
      method: "get",
      pathTemplate: "/v2/data-privacy/data-for-email-address",
      executionParameters: [{"name":"emailAddress","in":"query"},{"name":"cursor","in":"query"}],
      requestBodyContentType: undefined,
      securityRequirements: [{"basicAuth":[]}]
    }],
  • JSON Schema for tool input validation: requires 'emailAddress' (email format), optional 'cursor' (string). Used to generate Zod schema for runtime validation.
    inputSchema: {"type":"object","properties":{"emailAddress":{"type":"string","format":"email"},"cursor":{"type":"string"}},"required":["emailAddress"]},
  • MCP server request handler for CallToolRequestSchema that dispatches to the specific tool by looking up in toolDefinitionMap and calling 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: ${toolName}` }] };
      }
      return await executeApiTool(toolName, toolDefinition, toolArgs ?? {}, securitySchemes);
    });
  • Helper function to convert the tool's JSON inputSchema to a Zod schema for validation in the handler.
    function getZodSchemaFromJsonSchema(jsonSchema: any, toolName: string): z.ZodTypeAny {
        if (typeof jsonSchema !== 'object' || jsonSchema === null) { 
            return z.object({}).passthrough(); 
        }
        try {
            const zodSchemaString = jsonSchemaToZod(jsonSchema);
            const zodSchema = eval(zodSchemaString);
            if (typeof zodSchema?.parse !== 'function') { 
                throw new Error('Eval did not produce a valid Zod schema.'); 
            }
            return zodSchema as z.ZodTypeAny;
        } catch (err: any) {
            console.error(`Failed to generate/evaluate Zod schema for '${toolName}':`, err);
            return z.object({}).passthrough();
        }
    }
Behavior1/5

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 only hints at GDPR-related activities without detailing operational traits such as read-only vs. destructive actions, authentication needs, rate limits, or response format. This lack of information makes it inadequate for understanding how the tool behaves beyond its vague purpose.

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

Conciseness3/5

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

The description is brief with a single phrase, which is appropriately sized for its limited content. However, it is not front-loaded with critical information and lacks structure, as it only offers a vague hint without actionable details. While concise, it under-specifies rather than efficiently conveying value.

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?

Given the tool's complexity (involving GDPR data retrieval), lack of annotations, no output schema, and low schema coverage, the description is incomplete. It fails to address key aspects like what 'activities' entail, how results are returned, or any behavioral constraints. This leaves significant gaps for an agent to understand and use the tool effectively.

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?

The schema description coverage is 0%, meaning parameters are undocumented in the schema. The description does not add any meaning beyond what the schema provides—it mentions 'email address' but does not explain the 'cursor' parameter or provide context for either. With two parameters and no compensation in the description, this fails to clarify parameter roles or usage.

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

Purpose2/5

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

The description 'Activities for an email address (GDPR helper)' states a general purpose but lacks specificity. It mentions retrieving 'activities' related to GDPR compliance, which distinguishes it from sibling tools like user or call operations, but does not specify the exact verb (e.g., 'retrieve' or 'list') or resource details beyond email addresses. This is vague and borders on tautology with the tool name, which implies getting data privacy data.

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 GDPR compliance, implying usage for data privacy requests, but does not specify scenarios, prerequisites, or exclusions. Without explicit when/when-not instructions or named alternatives, it offers minimal usage context, leaving the agent to infer based on the GDPR hint alone.

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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