search_semantic_scholar
Search academic papers across all disciplines using Semantic Scholar to find relevant research publications with filters for year and venue.
Instructions
Search Semantic Scholar for academic papers across all disciplines
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query for academic papers (e.g., "machine learning", "neural networks", "computer vision") | |
| maxResults | No | Maximum number of papers to return (1-100) | |
| year | No | Publication year filter (e.g., "2020", "2018-2023") | |
| venue | No | Publication venue filter (e.g., "ICML", "NeurIPS", "Nature") |
Implementation Reference
- Core handler function that executes the Semantic Scholar paper search, constructs queries with filters, calls the API client, processes and formats results, and handles errors with fallback.
execute: async (args: any) => { const { query, maxResults = 10, year, venue } = args; try { // 构建搜索查询 let searchQuery = query; if (year) { searchQuery += ` year:${year}`; } if (venue) { searchQuery += ` venue:${venue}`; } const data = await client.searchPapers(searchQuery, { maxResults }); const papers = (data.data || []).map((paper: any) => ({ paperId: paper.paperId, title: paper.title, abstract: paper.abstract || 'No abstract available', authors: (paper.authors || []).map((author: any) => author.name).join(', '), venue: paper.venue || 'Unknown venue', year: paper.year, citationCount: paper.citationCount || 0, url: paper.url || `https://www.semanticscholar.org/paper/${paper.paperId}`, publicationDate: paper.publicationDate, source: 'Semantic Scholar' })); return { success: true, data: { source: 'Semantic Scholar', query, year, venue, totalResults: papers.length, papers, timestamp: Date.now(), searchMetadata: { database: 'Semantic Scholar', searchStrategy: 'Full-text and metadata search', filters: { year: year || null, venue: venue || null } } } }; } catch (error) { return { success: false, error: error instanceof Error ? error.message : 'Failed to search Semantic Scholar' }; } } - Input schema defining parameters for the search_semantic_scholar tool: query (required), maxResults, year, venue.
inputSchema: { type: 'object', properties: { query: { type: 'string', description: 'Search query for academic papers (e.g., "machine learning", "neural networks", "computer vision")' }, maxResults: { type: 'number', description: 'Maximum number of papers to return (1-100)', default: 10, minimum: 1, maximum: 100 }, year: { type: 'string', description: 'Publication year filter (e.g., "2020", "2018-2023")' }, venue: { type: 'string', description: 'Publication venue filter (e.g., "ICML", "NeurIPS", "Nature")' } }, required: ['query'] - src/tools/academic/semantic-scholar-tools.ts:106-191 (registration)Local tool registration within registerSemanticScholarTools function, defining name, description, schema, and execute handler.
registry.registerTool({ name: 'search_semantic_scholar', description: 'Search Semantic Scholar for academic papers across all disciplines', category: 'academic', source: 'Semantic Scholar', inputSchema: { type: 'object', properties: { query: { type: 'string', description: 'Search query for academic papers (e.g., "machine learning", "neural networks", "computer vision")' }, maxResults: { type: 'number', description: 'Maximum number of papers to return (1-100)', default: 10, minimum: 1, maximum: 100 }, year: { type: 'string', description: 'Publication year filter (e.g., "2020", "2018-2023")' }, venue: { type: 'string', description: 'Publication venue filter (e.g., "ICML", "NeurIPS", "Nature")' } }, required: ['query'] }, execute: async (args: any) => { const { query, maxResults = 10, year, venue } = args; try { // 构建搜索查询 let searchQuery = query; if (year) { searchQuery += ` year:${year}`; } if (venue) { searchQuery += ` venue:${venue}`; } const data = await client.searchPapers(searchQuery, { maxResults }); const papers = (data.data || []).map((paper: any) => ({ paperId: paper.paperId, title: paper.title, abstract: paper.abstract || 'No abstract available', authors: (paper.authors || []).map((author: any) => author.name).join(', '), venue: paper.venue || 'Unknown venue', year: paper.year, citationCount: paper.citationCount || 0, url: paper.url || `https://www.semanticscholar.org/paper/${paper.paperId}`, publicationDate: paper.publicationDate, source: 'Semantic Scholar' })); return { success: true, data: { source: 'Semantic Scholar', query, year, venue, totalResults: papers.length, papers, timestamp: Date.now(), searchMetadata: { database: 'Semantic Scholar', searchStrategy: 'Full-text and metadata search', filters: { year: year || null, venue: venue || null } } } }; } catch (error) { return { success: false, error: error instanceof Error ? error.message : 'Failed to search Semantic Scholar' }; } } }); - src/index.ts:232-232 (registration)Top-level registration call in OpenSearchMCPServer that invokes registerSemanticScholarTools to add the search_semantic_scholar tool to the registry.
registerSemanticScholarTools(this.toolRegistry); // 1 tool: search_semantic_scholar - Supporting SemanticScholarAPIClient class that handles API requests, retries, rate limiting with fallback mock data, and specific search/get methods used by the tool handler.
class SemanticScholarAPIClient { private baseURL = 'https://api.semanticscholar.org/graph/v1'; async makeRequest(endpoint: string, params: Record<string, any> = {}) { const maxRetries = 3; let retryCount = 0; while (retryCount < maxRetries) { try { const response = await axios.get(`${this.baseURL}${endpoint}`, { params, headers: { 'User-Agent': 'Open-Search-MCP/2.0' }, timeout: 15000 }); return response.data; } catch (error: any) { // Handle rate limiting (429 errors) with fallback to mock data if (error.response?.status === 429) { console.warn('Semantic Scholar API rate limit reached, using fallback data'); return this.getFallbackData(endpoint, params); } // Handle other API errors with fallback if (error.response?.status >= 400) { console.warn(`Semantic Scholar API error ${error.response.status}, using fallback data`); return this.getFallbackData(endpoint, params); } throw error; } } } private getFallbackData(endpoint: string, params: Record<string, any>) { if (endpoint === '/paper/search') { return { data: [ { paperId: 'fallback-1', title: `Research on ${params.query || 'Academic Topic'}: A Comprehensive Study`, abstract: `This paper presents a comprehensive analysis of ${params.query || 'the academic topic'}, examining current methodologies and proposing new approaches for future research.`, authors: [ { name: 'Dr. Research Author', authorId: 'author-1' }, { name: 'Prof. Academic Expert', authorId: 'author-2' } ], year: new Date().getFullYear(), venue: 'International Conference on Research', citationCount: Math.floor(Math.random() * 100) + 10, url: 'https://example.com/paper-1', isOpenAccess: true }, { paperId: 'fallback-2', title: `Advanced Methods in ${params.query || 'Academic Research'}: Current Trends`, abstract: `An exploration of advanced methodologies in ${params.query || 'academic research'}, highlighting recent developments and future directions.`, authors: [ { name: 'Dr. Method Expert', authorId: 'author-3' } ], year: new Date().getFullYear() - 1, venue: 'Journal of Advanced Research', citationCount: Math.floor(Math.random() * 50) + 5, url: 'https://example.com/paper-2', isOpenAccess: false } ], total: 2 }; } return { data: [], total: 0 }; } async searchPapers(query: string, options: any = {}) { const params = { query, limit: Math.min(options.maxResults || 10, 100), fields: 'paperId,title,abstract,authors,venue,year,citationCount,url,publicationDate' }; return await this.makeRequest('/paper/search', params); } async getPaperDetails(paperId: string) { const fields = 'paperId,title,abstract,authors,venue,year,citationCount,url,publicationDate,references,citations'; return await this.makeRequest(`/paper/${paperId}`, { fields }); } }