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reetp14

OpenAlex MCP Server

by reetp14

search_topics

Search research topics and concepts in scholarly databases using full-text queries, filters, sorting, and pagination to find relevant academic subjects.

Instructions

Search research topics (formerly concepts)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoFull-text search query
filterNoKey:value OpenAlex filters. Supports entity attributes (e.g., 'domain.id', 'level'), IDs, and convenience filters (e.g., 'display_name.search'). Example: 'domain.id:D1,level:0'
sortNoSort field with optional :desc
pageNoPage number
per_pageNoResults per page (max 200)
cursorNoCursor for deep pagination
group_byNoGroup results by field
selectNoFields to return
sampleNoRandom sample size
seedNoRandom seed
mailtoNoEmail for rate limits
api_keyNoPremium API key

Implementation Reference

  • The core handler function for the 'search_topics' tool. It calls makeOpenAlexRequest on the '/topics' endpoint with input args and returns the JSON response formatted as MCP text content.
    export async function searchTopics(args: any) {
        return {
            content: [{
                    type: "text",
                    text: JSON.stringify(await makeOpenAlexRequest("/topics", args), null, 2)
                }]
        };
    }
  • Input schema for the 'search_topics' tool as defined in the ListTools handler response.
    {
        name: "search_topics",
        description: "Search research topics (formerly concepts)",
        inputSchema: {
            type: "object",
            properties: {
                search: { type: "string", description: "Full-text search query" },
                filter: { type: "string", description: "Key:value OpenAlex filters. Supports entity attributes (e.g., 'domain.id', 'level'), IDs, and convenience filters (e.g., 'display_name.search'). Example: 'domain.id:D1,level:0'" },
                sort: { type: "string", description: "Sort field with optional :desc" },
                page: { type: "number", description: "Page number" },
                per_page: { type: "number", description: "Results per page (max 200)" },
                cursor: { type: "string", description: "Cursor for deep pagination" },
                group_by: { type: "string", description: "Group results by field" },
                select: { type: "string", description: "Fields to return" },
                sample: { type: "number", description: "Random sample size" },
                seed: { type: "number", description: "Random seed" },
                mailto: { type: "string", description: "Email for rate limits" },
                api_key: { type: "string", description: "Premium API key" }
            }
        }
    },
  • src/index.ts:289-290 (registration)
    Registration in the CallToolRequest switch statement that dispatches to the searchTopics handler.
    case "search_topics":
        return await searchTopics(args);
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic action ('Search research topics') without mentioning rate limits, authentication requirements (though api_key parameter hints at premium access), pagination behavior, or expected response format. For a search tool with 12 parameters, this is a significant gap in behavioral context.

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 extremely concise - a single parenthetical phrase that efficiently communicates the resource type and historical context ('formerly concepts'). Every word earns its place, and the information is front-loaded with no wasted verbiage.

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?

For a complex search tool with 12 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a 'research topic', what fields are searchable, the expected return format, or how results are structured. The agent would need to infer much from parameter names alone.

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 description coverage is 100%, so the schema already documents all 12 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 as 'Search research topics (formerly concepts)', which provides a specific verb ('Search') and resource ('research topics'). It distinguishes the resource type from siblings like search_authors or search_works, but doesn't explicitly differentiate functionality beyond the resource type.

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. While the resource type ('research topics') implicitly suggests usage for topic-related searches, there's no explicit mention of when to choose this over other search tools (like search_works for publications) or get_entity for specific topic retrieval.

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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