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MoralisWeb3

Moralis MCP Server

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by MoralisWeb3

evm_getmultipletokenanalytics

Fetch analytics for multiple tokens including volume, transactions, liquidity, and FDV trends across blockchain networks to analyze token performance.

Instructions

Fetch analytics for multiple tokens, including buy volume, sell volume, buyers, sellers, transactions, liquidity and FDV trends over time. Accepts an array of up to 200 tokens, each requiring chain and tokenAddress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestBodyYesBody

Implementation Reference

  • Core handler that executes the tool logic for 'evm_getmultipletokenanalytics' and all API-derived tools. Validates input using Zod from JSON schema, constructs HTTP request (URL, params, headers, body, auth), calls Moralis API with axios, formats JSON response or error.
    export async function executeApiTool(
      toolName: string,
      definition: McpToolDefinition,
      toolArgs: JsonObject,
      allSecuritySchemes: Record<string, any>,
      token?: string,
    ): Promise<CallToolResult> {
      try {
        // Validate arguments against the input schema
        let validatedArgs: JsonObject;
        try {
          const zodSchema = getZodSchemaFromJsonSchema(
            definition.inputSchema,
            toolName,
          );
          const argsToParse =
            typeof toolArgs === 'object' && toolArgs !== null ? toolArgs : {};
          validatedArgs = zodSchema.parse(argsToParse);
        } catch (error: unknown) {
          if (error instanceof ZodError) {
            const validationErrorMessage = `Invalid arguments for tool '${toolName}': ${error.errors.map((e) => `${e.path.join('.')} (${e.code}): ${e.message}`).join(', ')}`;
            return { content: [{ type: 'text', text: validationErrorMessage }] };
          } else {
            const errorMessage =
              error instanceof Error ? error.message : String(error);
            return {
              content: [
                {
                  type: 'text',
                  text: `Internal error during validation setup: ${errorMessage}`,
                },
              ],
            };
          }
        }
    
        // Prepare URL, query parameters, headers, and request body
        let urlPath = definition.pathTemplate;
        const queryParams: Record<string, any> = {};
        const headers: Record<string, string> = {
          Accept: 'application/json',
          'X-Moralis-Platform': 'MCP',
        };
        let requestBodyData: any = undefined;
    
        // Apply parameters to the URL path, query, or headers
        definition.executionParameters.forEach((param) => {
          const value = validatedArgs[param.name];
          if (typeof value !== 'undefined' && value !== null) {
            if (param.in === 'path') {
              urlPath = urlPath.replace(
                `{${param.name}}`,
                encodeURIComponent(String(value)),
              );
            } else if (param.in === 'query') {
              queryParams[param.name] = value;
            } else if (param.in === 'header') {
              headers[param.name.toLowerCase()] = String(value);
            }
          }
        });
    
        // Ensure all path parameters are resolved
        if (urlPath.includes('{')) {
          throw new Error(`Failed to resolve path parameters: ${urlPath}`);
        }
    
        // Construct the full URL
        const requestUrl = `${definition.baseUrl}${urlPath}`;
    
        // Handle request body if needed
        if (
          definition.requestBodyContentType &&
          typeof validatedArgs['requestBody'] !== 'undefined'
        ) {
          requestBodyData = validatedArgs['requestBody'];
          headers['content-type'] = definition.requestBodyContentType;
        }
    
        // Apply security requirements if available
        // Security requirements use OR between array items and AND within each object
        const appliedSecurity = definition.securityRequirements?.find((req) => {
          // Try each security requirement (combined with OR)
          return Object.entries(req).every(([schemeName, scopesArray]) => {
            const scheme = allSecuritySchemes[schemeName];
            if (!scheme) return false;
    
            // API Key security (header, query, cookie)
            if (scheme.type === 'apiKey') {
              return !!token || !!Config.MORALIS_API_KEY;
            }
    
            return false;
          });
        });
    
        // If we found matching security scheme(s), apply them
        if (appliedSecurity) {
          // Apply each security scheme from this requirement (combined with AND)
          for (const [schemeName, scopesArray] of Object.entries(appliedSecurity)) {
            const scheme = allSecuritySchemes[schemeName];
    
            // API Key security
            if (scheme?.type === 'apiKey') {
              const apiKey = token || Config.MORALIS_API_KEY;
              if (apiKey) {
                if (scheme.in === 'header') {
                  headers[scheme.name.toLowerCase()] = apiKey;
                  console.error(
                    `Applied API key '${schemeName}' in header '${scheme.name}'`,
                  );
                }
              }
            }
          }
        }
        // Log warning if security is required but not available
        else if (definition.securityRequirements?.length > 0) {
          // First generate a more readable representation of the security requirements
          const securityRequirementsString = definition.securityRequirements
            .map((req) => {
              const parts = Object.entries(req)
                .map(([name, scopesArray]) => {
                  const scopes = scopesArray as string[];
                  if (scopes.length === 0) return name;
                  return `${name} (scopes: ${scopes.join(', ')})`;
                })
                .join(' AND ');
              return `[${parts}]`;
            })
            .join(' OR ');
    
          console.warn(
            `Tool '${toolName}' requires security: ${securityRequirementsString}, but no suitable credentials found.`,
          );
        }
    
        // Prepare the axios request configuration
        const config: AxiosRequestConfig = {
          method: definition.method.toUpperCase(),
          url: requestUrl,
          params: queryParams,
          headers: headers,
          ...(requestBodyData !== undefined && { data: requestBodyData }),
        };
    
        // Log request info to stderr (doesn't affect MCP output)
        console.error(
          `Executing tool "${toolName}": ${config.method} ${config.url}`,
        );
    
        // Execute the request
        const response = await axios(config);
    
        // Process and format the response
        let responseText = '';
        const contentType = response.headers['content-type']?.toLowerCase() || '';
    
        // Handle JSON responses
        if (
          contentType.includes('application/json') &&
          typeof response.data === 'object' &&
          response.data !== null
        ) {
          try {
            responseText = JSON.stringify(response.data, null, 2);
          } catch (e) {
            responseText = '[Stringify Error]';
          }
        }
        // Handle string responses
        else if (typeof response.data === 'string') {
          responseText = response.data;
        }
        // Handle other response types
        else if (response.data !== undefined && response.data !== null) {
          responseText = String(response.data);
        }
        // Handle empty responses
        else {
          responseText = `(Status: ${response.status} - No body content)`;
        }
    
        // Return formatted response
        return {
          content: [
            {
              type: 'text',
              text: `API Response (Status: ${response.status}):\n${responseText}`,
            },
          ],
        };
      } catch (error: unknown) {
        // Handle errors during execution
        let errorMessage: string;
    
        // Format Axios errors specially
        if (axios.isAxiosError(error)) {
          errorMessage = formatApiError(error);
        }
        // Handle standard errors
        else if (error instanceof Error) {
          errorMessage = error.message;
        }
        // Handle unexpected error types
        else {
          errorMessage = `Unexpected error: ${String(error)}`;
        }
    
        // Log error to stderr
        console.error(
          `Error during execution of tool '${toolName}':`,
          errorMessage,
        );
    
        // Return error message to client
        return { content: [{ type: 'text', text: errorMessage }] };
      }
    }
  • src/server.ts:26-44 (registration)
    Registers all tools from EVM OpenAPI spec by fetching/dereferencing spec, extracting tools with 'evm_' prefix using extractToolsFromApi, applying blacklist, mapping to toolDefinitionMap used by MCP handlers. 'evm_getmultipletokenanalytics' is created here if present in spec.
    async function mapToolDefinitions(config: SchemaConfig) {
      const spec = (await getSpec(config.specUrl)) as OpenAPIV3DocumentX;
      const api = (await SwaggerParser.dereference(spec)) as OpenAPIV3DocumentX;
    
      const tools = extractToolsFromApi(api, config.prefix);
      const blacklist = Array.isArray(api['x-mcp-blacklist'])
        ? api['x-mcp-blacklist'].map((e) => `${config.prefix}${e.toLowerCase()}`)
        : [];
    
      const toolDefinitionMap: Record<string, McpToolDefinition> = {};
      for (const tool of tools) {
        if (blacklist.includes(tool.name)) continue;
        toolDefinitionMap[tool.name] = {
          ...tool,
          baseUrl: config.baseUrl,
        };
      }
      return toolDefinitionMap;
    }
  • Helper that parses OpenAPI document to create McpToolDefinition for each operation, adding prefix to operationId-based name. This generates the definition for 'evm_getmultipletokenanalytics' from the corresponding path/method in Moralis EVM spec.
    export function extractToolsFromApi(
      api: OpenAPIV3DocumentX,
      prefix?: string
    ): McpToolDefinition[] {
      const tools: McpToolDefinition[] = [];
      const usedNames = new Set<string>();
      const globalSecurity = api.security || [];
    
      if (!api.paths) return tools;
    
      for (const [path, pathItem] of Object.entries(api.paths)) {
        if (!pathItem) continue;
    
        for (const method of Object.values(OpenAPIV3.HttpMethods)) {
          const operation = pathItem[method];
          if (!operation) continue;
    
          // Generate a unique name for the tool
          let baseName = operation.operationId || generateOperationId(method, path);
          if (!baseName) continue;
    
          // Sanitize the name to be MCP-compatible (only a-z, 0-9, _, -)
          baseName = baseName
            .replace(/\./g, '_')
            .replace(/[^a-z0-9_-]/gi, '_')
            .toLowerCase();
    
          let finalToolName = baseName;
          let counter = 1;
          while (usedNames.has(finalToolName)) {
            finalToolName = `${baseName}_${counter++}`;
          }
          usedNames.add(finalToolName);
    
          // Get or create a description
          const description =
            operation.description ||
            operation.summary ||
            `Executes ${method.toUpperCase()} ${path}`;
    
          const prompt = operation['x-mcp-prompt'];
    
          // Generate input schema and extract parameters
          const { inputSchema, parameters, requestBodyContentType } =
            generateInputSchemaAndDetails(operation);
    
          // Extract parameter details for execution
          const executionParameters = parameters.map((p) => ({
            name: p.name,
            in: p.in,
          }));
    
          // Determine security requirements
          const securityRequirements =
            operation.security === null
              ? globalSecurity
              : operation.security || globalSecurity;
    
          // Create the tool definition
          tools.push({
            name: prefix + finalToolName,
            description,
            inputSchema,
            method,
            pathTemplate: path,
            parameters,
            executionParameters,
            requestBodyContentType,
            securityRequirements,
            operationId: baseName,
            prompt,
          });
        }
      }
    
      return tools;
    }
  • Generates the inputSchema (JSON Schema object) for the tool from OpenAPI operation's parameters and requestBody. Used to create MCP tool's inputSchema and enable Zod validation.
    export function generateInputSchemaAndDetails(
      operation: OpenAPIV3.OperationObject,
    ): {
      inputSchema: JSONSchema7 | boolean;
      parameters: OpenAPIV3.ParameterObject[];
      requestBodyContentType?: string;
    } {
      const properties: { [key: string]: JSONSchema7 | boolean } = {};
      const required: string[] = [];
    
      // Process parameters
      const allParameters: OpenAPIV3.ParameterObject[] = Array.isArray(
        operation.parameters,
      )
        ? operation.parameters.map((p) => p as OpenAPIV3.ParameterObject)
        : [];
    
      allParameters.forEach((param) => {
        if (!param.name || !param.schema) return;
    
        const paramSchema = mapOpenApiSchemaToJsonSchema(
          param.schema as OpenAPIV3.SchemaObject,
        );
        if (typeof paramSchema === 'object') {
          paramSchema.description = param.description || paramSchema.description;
        }
    
        properties[param.name] = paramSchema;
        if (param.required) required.push(param.name);
      });
    
      // Process request body (if present)
      let requestBodyContentType: string | undefined = undefined;
    
      if (operation.requestBody) {
        const opRequestBody = operation.requestBody as OpenAPIV3.RequestBodyObject;
        const jsonContent = opRequestBody.content?.['application/json'];
        const firstContent = opRequestBody.content
          ? Object.entries(opRequestBody.content)[0]
          : undefined;
    
        if (jsonContent?.schema) {
          requestBodyContentType = 'application/json';
          const bodySchema = mapOpenApiSchemaToJsonSchema(
            jsonContent.schema as OpenAPIV3.SchemaObject,
          );
    
          if (typeof bodySchema === 'object') {
            bodySchema.description =
              opRequestBody.description ||
              bodySchema.description ||
              'The JSON request body.';
          }
    
          properties['requestBody'] = bodySchema;
          if (opRequestBody.required) required.push('requestBody');
        } else if (firstContent) {
          const [contentType] = firstContent;
          requestBodyContentType = contentType;
    
          properties['requestBody'] = {
            type: 'string',
            description:
              opRequestBody.description ||
              `Request body (content type: ${contentType})`,
          };
    
          if (opRequestBody.required) required.push('requestBody');
        }
      }
    
      // Combine everything into a JSON Schema
      const inputSchema: JSONSchema7 = {
        type: 'object',
        properties,
        ...(required.length > 0 && { required }),
      };
    
      return { inputSchema, parameters: allParameters, requestBodyContentType };
    }
  • EVM configuration defining 'evm_' prefix for tool names, baseUrl for API calls, and specUrl for the OpenAPI document containing the 'getmultipletokenanalytics' operation.
    evm:  {
      prefix: 'evm_',
      baseUrl:
        process.env.API_BASE_URL || 'https://deep-index.moralis.io/api/v2.2',
      specUrl:
        process.env.API_SPEC_URL ||
        'https://deep-index.moralis.io/api-docs-2.2/v2.2/swagger.json',
    },
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. It mentions the array limit (up to 200 tokens) and required fields (chain, tokenAddress), but does not disclose behavioral traits such as rate limits, authentication needs, response format, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its operation.

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 front-loaded with key information (purpose and parameters) in two sentences, with no wasted words. It efficiently conveys the tool's function and input requirements, though it could be slightly more structured for clarity.

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 and no output schema, the description is incomplete. It lacks details on response format, error conditions, rate limits, and authentication requirements. For a tool fetching analytics for multiple tokens, this leaves the agent without sufficient context to handle the tool effectively.

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?

Schema description coverage is 100%, with the schema fully documenting the tokens array, chain, and tokenAddress parameters. The description adds minimal value beyond the schema, mentioning the array limit and required fields, which are already covered. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose5/5

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

The description clearly states the verb ('Fetch') and resource ('analytics for multiple tokens'), specifying the analytics types (buy volume, sell volume, buyers, sellers, transactions, liquidity, FDV trends over time). It distinguishes from siblings like evm_gettimeseriestokenanalytics by emphasizing batch processing of multiple tokens rather than time-series for a single token.

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

Usage Guidelines3/5

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

The description implies usage for batch token analytics but does not explicitly state when to use this tool versus alternatives like evm_gettimeseriestokenanalytics or evm_gettokenmetadata. It mentions the array limit of up to 200 tokens, which provides some context, but lacks explicit guidance on prerequisites or comparisons to sibling tools.

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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