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MoralisWeb3

Moralis MCP Server

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by MoralisWeb3

evm_gettokenmetadata

Retrieve ERC20 token metadata including name, symbol, decimals, logo, total supply, categories, and spam status for contract addresses across multiple blockchain networks.

Instructions

Retrieve metadata (name, symbol, decimals, logo) for an ERC20 token contract, as well as off-chain metadata, total supply, categories, logos, spam status and more.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoThe chain to queryeth
addressesYesThe addresses to get metadata for

Implementation Reference

  • The core handler function that implements the logic for executing the 'evm_gettokenmetadata' tool (and all other dynamic tools). It validates inputs with Zod schema derived from OpenAPI, builds the HTTP request using the tool's pathTemplate, method, parameters, applies API key auth from config or token, calls axios to Moralis EVM API, processes JSON response, and returns formatted text content.
    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:97-119 (registration)
    Registers the MCP 'tools/call' request handler. For 'evm_gettokenmetadata', it retrieves the tool definition from the map and invokes the generic executeApiTool handler.
    CallToolRequestSchema,
    async (request: CallToolRequest, c): Promise<CallToolResult> => {
      const { name: toolName, arguments: toolArgs } = request.params;
      const toolDefinition = toolDefinitionMap[toolName];
      if (!toolDefinition) {
        console.error(`Error: Unknown tool requested: ${toolName}`);
        return {
          content: [
            {
              type: 'text',
              text: `Error: Unknown tool requested: ${toolName}`,
            },
          ],
        };
      }
      return executeApiTool(
        toolName,
        toolDefinition,
        toolArgs ?? {},
        securitySchemes,
        c.authInfo?.token,
      );
    },
  • src/server.ts:26-43 (registration)
    Dynamically generates and registers tool definitions by fetching/parsing OpenAPI spec from Moralis EVM API, extracting tools with 'evm_' prefix via extractToolsFromApi (which creates 'evm_gettokenmetadata' from matching operation), building the toolDefinitionMap used by handlers.
    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;
  • Generates the inputSchema (JSON Schema) for the tool definition of 'evm_gettokenmetadata' from the OpenAPI operation's parameters and requestBody. This schema is used for MCP tool description and runtime 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 };
  • Configuration for EVM tools, providing 'evm_' prefix (so gettokenmetadata -> evm_gettokenmetadata), baseUrl for API calls, and specUrl from which the tool definitions including schemas and paths are extracted.
    const configs: Record<string, SchemaConfig> = {
      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 of behavioral disclosure. It mentions retrieving metadata but doesn't disclose critical traits: whether this is a read-only operation (implied but not stated), rate limits, authentication needs, error handling (e.g., for invalid addresses), pagination (though addresses are limited to 10), or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves beyond the basic retrieval 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 that front-loads the core purpose ('Retrieve metadata...') and lists key metadata fields. There's no wasted verbiage or redundancy. However, it could be slightly more structured by separating core vs. extended metadata, but this is minor. It earns a 4 for being appropriately sized and direct.

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 (ERC20 token metadata retrieval with multiple fields), lack of annotations, and no output schema, the description is incomplete. It lists metadata types but doesn't cover behavioral aspects (e.g., rate limits, errors), response structure, or usage context. For a tool with 2 parameters and rich potential output, more detail is needed to help an agent invoke it correctly without structured output guidance.

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 clear descriptions for both parameters ('The chain to query' and 'The addresses to get metadata for'). The description adds no parameter-specific semantics beyond what the schema provides—it doesn't explain address format (e.g., checksummed), chain selection implications, or the meaning of retrieving metadata for multiple addresses. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 ('Retrieve') and resource ('metadata for an ERC20 token contract'), and lists specific metadata fields (name, symbol, decimals, logo, off-chain metadata, total supply, categories, spam status). It distinguishes from siblings like evm_gettokenholders or evm_gettokenprices by focusing on metadata retrieval rather than holders, pairs, or analytics. However, it doesn't explicitly differentiate from evm_getnftmetadata (which handles NFTs) or solana_gettokenmetadata (which handles Solana tokens), though the ERC20 specification provides some implicit distinction.

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 doesn't mention when to choose it over evm_getfilteredtokens (which might include metadata), evm_searchtokens (for discovery), or evm_gettokenscore (for scoring). There are no exclusions, prerequisites, or context about typical use cases (e.g., for token verification or display). The agent must infer usage from the purpose 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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