Skip to main content
Glama
metehan777

Semrush MCP Server

by metehan777

domain_adwords

Analyze Google Ads keywords for any domain to identify paid search strategies and competitor advertising approaches.

Instructions

Get paid search (Google Ads) keywords for a domain

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes
databaseNo
limitNo

Implementation Reference

  • Handler logic for the 'domain_adwords' tool: parses input arguments using the schema and calls the Semrush API with appropriate parameters to fetch paid search keywords data.
    case 'domain_adwords': {
      const { domain, database, limit } = DomainAdwordsSchema.parse(args);
      data = await callSemrushAPI('domain_adwords', {
        domain,
        database,
        display_limit: limit,
        export_columns: 'Ph,Po,Pp,Pd,Nq,Cp,Ur,Tr,Tc,Co,Nr,Td,Avg,Sym,Sp',
      });
      break;
  • Zod schema defining the input parameters for the domain_adwords tool: domain (required), database (default 'us'), and limit (default 10).
    const DomainAdwordsSchema = z.object({
      domain: z.string().describe('Domain to analyze'),
      database: z.string().default('us').describe('Database code'),
      limit: z.coerce.number().default(10).describe('Number of results'),
    });
  • src/index.ts:219-227 (registration)
    Tool registration in the ListTools response, specifying name, description, and inputSchema based on DomainAdwordsSchema.
    {
      name: 'domain_adwords',
      description: 'Get paid search (Google Ads) keywords for a domain',
      inputSchema: {
        type: 'object',
        properties: DomainAdwordsSchema.shape,
        required: ['domain'],
      },
    },
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 states the tool 'gets' data, implying a read-only operation, but doesn't cover critical aspects like authentication needs, rate limits, error handling, or response format. For a tool with 3 parameters and no annotations, this leaves significant gaps in understanding its behavior.

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 a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently conveys the essential information without unnecessary elaboration.

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 tool has 3 parameters with 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't address parameter meanings, behavioral traits, or return values, making it inadequate for an AI agent to fully understand and invoke the tool correctly.

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?

Schema description coverage is 0%, meaning none of the 3 parameters have descriptions in the schema. The tool description doesn't mention any parameters or add meaning beyond the schema. It fails to explain what 'domain,' 'database,' or 'limit' mean in context, leaving them undocumented.

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 tool's purpose: 'Get paid search (Google Ads) keywords for a domain.' It specifies the action ('get'), resource ('keywords'), and context ('paid search/Google Ads for a domain'). However, it doesn't explicitly differentiate from sibling tools like 'keyword_overview' or 'related_keywords,' which might also handle keywords.

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 sibling tools like 'keyword_overview' or 'domain_organic_search,' nor does it specify use cases, prerequisites, or exclusions. 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.

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/metehan777/semrush-mcp'

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