Skip to main content
Glama
alexleventer

Marketo MCP Server

by alexleventer

marketo_get_emails

List Marketo email assets filtered by approval status and paginated. Returns email metadata including subject, from address, and template ID.

Instructions

List email assets in Marketo. Filter by approval status (approved/draft) and paginate with maxReturn/offset. Returns email metadata including subject line, from address, and template ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxReturnNo
offsetNo
statusNo

Implementation Reference

  • The handler function for the 'marketo_get_emails' tool. It constructs query params (maxReturn, offset, status) and calls the Marketo Asset API GET /asset/v1/emails.json endpoint.
    tool(async ({ maxReturn = 200, offset = 0, status }) => {
      const params = new URLSearchParams({
        maxReturn: maxReturn.toString(),
        offset: offset.toString(),
      });
      if (status) params.append('status', status);
      return makeApiRequest(`/asset/v1/emails.json?${params.toString()}`, 'GET');
    })
  • Input schema for the 'marketo_get_emails' tool: optional maxReturn (number), offset (number), and status (enum: approved/draft), validated with Zod.
    {
      maxReturn: z.number().optional(),
      offset: z.number().optional(),
      status: z.enum(['approved', 'draft']).optional(),
    },
  • src/index.ts:500-516 (registration)
    Registration of the 'marketo_get_emails' tool on the MCP server via server.tool(), including its name, description, input schema, and handler.
    server.tool(
      'marketo_get_emails',
      'List email assets in Marketo. Filter by approval status (approved/draft) and paginate with maxReturn/offset. Returns email metadata including subject line, from address, and template ID.',
      {
        maxReturn: z.number().optional(),
        offset: z.number().optional(),
        status: z.enum(['approved', 'draft']).optional(),
      },
      tool(async ({ maxReturn = 200, offset = 0, status }) => {
        const params = new URLSearchParams({
          maxReturn: maxReturn.toString(),
          offset: offset.toString(),
        });
        if (status) params.append('status', status);
        return makeApiRequest(`/asset/v1/emails.json?${params.toString()}`, 'GET');
      })
    );
  • The makeApiRequest helper function used by the handler to execute HTTP requests to Marketo's REST API with proper auth headers.
    async function makeApiRequest(
      endpoint: string,
      method: string,
      data?: any,
      contentType: string = 'application/json'
    ) {
      const token = await tokenManager.getToken();
      const headers: Record<string, string> = {
        Authorization: `Bearer ${token}`,
      };
    
      if (contentType) {
        headers['Content-Type'] = contentType;
      }
    
      try {
        const response = await axios({
          url: `${MARKETO_BASE_URL}${endpoint}`,
          method,
          data:
            contentType === 'application/x-www-form-urlencoded'
              ? new URLSearchParams(data).toString()
              : data,
          headers,
        });
        return response.data;
      } catch (error: any) {
        console.error('API request failed:', error.response?.data || error.message);
        throw error;
      }
    }
  • The tool() wrapper function that wraps each handler to catch errors and return a standardized MCP content response.
    function tool<T>(handler: (args: T) => Promise<unknown>) {
      return async (args: T) => {
        try {
          const response = await handler(args);
          return {
            content: [{ type: 'text' as const, text: JSON.stringify(response, null, 2) }],
          };
        } catch (error: any) {
          return {
            content: [
              {
                type: 'text' as const,
                text: `Error: ${error.response?.data?.message || error.message}`,
              },
            ],
            isError: true,
          };
        }
      };
    }
Behavior3/5

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

No annotations provided; description lists return fields (subject, from, template ID) but doesn't explicitly state read-only nature or other behavioral traits like authentication or rate limits.

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?

Two sentences, front-loaded with purpose, no unnecessary words.

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

Completeness4/5

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

Returns field info compensates for no output schema; covers filtering and pagination; could mention scope (all emails?), but sufficient for a list tool.

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 coverage is 0%; description adds meaning for status (approved/draft) and mentions pagination, but does not fully explain maxReturn and offset behavior.

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?

Clearly states 'List email assets in Marketo' with a specific verb and resource. Distinguishes from sibling tools like marketo_get_email_by_id.

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

Usage Guidelines4/5

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

Implicitly tells when to use for listing emails with filtering and pagination, but lacks explicit comparison to alternatives or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/alexleventer/marketo-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server