get_relevant_context
Retrieve targeted code snippets by describing your needs in natural language to find relevant programming context efficiently.
Instructions
Get code context relevant to a natural language query. Returns minimal, targeted code snippets.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language description of what you need context for | |
| maxTokens | No | Maximum tokens to return (approximate). Default: 4000 |
Implementation Reference
- src/retriever.ts:126-165 (handler)Implementation of getRelevantContext method which performs the search and prepares the response.
async getRelevantContext(query: string, maxTokens: number): Promise<string> { // Use advanced search engine const allSymbols = this.getAllSymbols(); const files = this.indexer.getAllFiles(); const searchOptions: SearchOptions = { maxResults: 50, // Get more candidates, then filter by tokens fuzzyThreshold: 0.7, includeCodeBodies: true, includeComments: true, boostExactMatches: true, }; const matches = CodeSearchEngine.search(query, allSymbols, files, searchOptions); if (matches.length === 0) { // Provide helpful suggestions const queryTokens = CodeSearchEngine.tokenize(query); const suggestions = this.getSuggestions(queryTokens); return `No relevant context found for query: "${query}"\n\n${ suggestions.length > 0 ? `Did you mean one of these?\n${suggestions.map(s => ` - ${s}`).join('\n')}\n\n` : '' }Try:\n- Using more specific terms\n- Checking for typos (fuzzy search is active but needs some similarity)\n- Using search_code for regex pattern matching\n- Using find_symbol for exact symbol lookup`; } // Build response within token limit let result = `š Found ${matches.length} relevant results for: "${query}"\n\n`; let estimatedTokens = this.estimateTokens(result); let included = 0; for (const match of matches) { const formattedMatch = this.formatSearchMatch(match, true); const matchTokens = this.estimateTokens(formattedMatch); if (estimatedTokens + matchTokens > maxTokens) { result += `\n... (${matches.length - included} more results available, but truncated to stay within ${maxTokens} token limit)`; break; } - src/index.ts:144-152 (registration)Registration of the get_relevant_context MCP tool.
name: 'get_relevant_context', description: 'ā PREFERRED SEARCH: Use this INSTEAD OF Grep for finding code by description. Natural language search with BM25 ranking. Saves 70-90% tokens vs reading files directly. Examples: "authentication middleware", "payment processing", "gacha spin mechanics". Returns only relevant code snippets with relevance scores.', inputSchema: { type: 'object', properties: { query: { type: 'string', description: 'Natural language description of what you need (e.g., "user authentication flow", "error handling logic")', },