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SurfRankAI

SurfRank MCP Server

by SurfRankAI

list_keyword_research

Retrieve a list of previous keyword research runs, filtered by project, to review past AI visibility analyses.

Instructions

List past keyword research runs, optionally filtered by project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
websiteIdNo
pageNo1-based page index
limitNoResults per page (default 20)

Implementation Reference

  • The handler function for list_keyword_research. It calls api.get with the /keyword-research endpoint, passing optional websiteId, page, and limit query parameters.
    handler: async ({ websiteId, page, limit }) =>
      api.get('/keyword-research', { websiteId, page, limit }),
  • Input schema defining optional parameters: websiteId (string), page (number, 1-based), limit (number, default 20).
    inputSchema: {
      type: 'object',
      properties: {
        websiteId: { type: 'string' },
        page: { type: 'number', description: '1-based page index' },
        limit: { type: 'number', description: 'Results per page (default 20)' },
      },
    },
  • Tool definition object with name 'list_keyword_research', description, inputSchema, and handler — part of the keywordResearchTools array exported from this file.
      {
        name: 'list_keyword_research',
        description: 'List past keyword research runs, optionally filtered by project.',
        inputSchema: {
          type: 'object',
          properties: {
            websiteId: { type: 'string' },
            page: { type: 'number', description: '1-based page index' },
            limit: { type: 'number', description: 'Results per page (default 20)' },
          },
        },
        handler: async ({ websiteId, page, limit }) =>
          api.get('/keyword-research', { websiteId, page, limit }),
      },
      {
        name: 'get_keyword_research',
        description: 'Get a single keyword-research run by ID.',
        inputSchema: {
          type: 'object',
          properties: { researchId: { type: 'string' } },
          required: ['researchId'],
        },
        handler: async ({ researchId }) => api.get(`/keyword-research/${researchId}`),
      },
    ];
  • src/index.js:31-39 (registration)
    keywordResearchTools (including list_keyword_research) are spread into the ALL_TOOLS array which is then registered with the MCP server via ListToolsRequestSchema and CallToolRequestSchema handlers.
    const ALL_TOOLS = [
      ...projectTools,
      ...keywordTools,
      ...reportTools,
      ...quickTestTools,
      ...keywordResearchTools,
      ...competitorTools,
      ...opportunityTools,
    ];
  • The api.get helper used by the handler to make the HTTP GET request to the SurfRank API.
    export const api = {
      get: (path, query) => request('GET', path, { query }),
      post: (path, body) => request('POST', path, { body }),
      patch: (path, body) => request('PATCH', path, { body }),
      delete: (path) => request('DELETE', path),
    };
Behavior2/5

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

No annotations are provided, so the description must carry full burden. It only states the basic purpose without disclosing behavioral traits such as read-only nature, authentication requirements, rate limits, or handling of empty results. This is insufficient for a tool with no annotations.

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?

A single sentence of 12 words that is front-loaded with verb and resource. Every word earns its place; no redundancy or unnecessary detail.

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

Completeness3/5

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

For a list tool with pagination parameters and no output schema, the description lacks details like default ordering, pagination behavior, and return fields. It provides minimal context beyond the core function, which is adequate but not thorough.

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?

The schema covers 67% of parameters with descriptions (page and limit). The description adds no additional parameter context, and the undocumented 'websiteId' parameter is not explained. Baseline 3 is appropriate as schema covers most parameters.

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 uses the specific verb 'list' and resource 'keyword research runs', clearly distinguishing it from siblings like 'get_keyword_research' (singular) and 'research_keyword' (create). The optional filter by project is also mentioned.

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?

The description clearly states the function (list past runs) and the optional filter. However, it does not explicitly mention when not to use this tool or compare it to alternatives like 'get_keyword_research' or 'research_keyword', leaving some ambiguity.

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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