Helios-9 MCP Server

Instructions

Implementation Reference

• src/tools/documents.ts:352-375 (handler)

  The core handler function for the 'get_document_context' tool. It fetches the document by ID, performs content analysis, extracts links, generates AI context, finds related documents, and returns comprehensive context information.
  export const getDocumentContext = requireAuth(async (args: any) => { const { document_id } = GetDocumentSchema.parse(args) logger.info('Getting document context', { document_id }) const document = await supabaseService.getDocument(document_id) // Analyze document content and extract metadata const contentAnalysis = analyzeDocumentContentHelper(document.content, document.document_type) const linkAnalysis = extractDocumentLinks(document.content) const aiContext = extractAIContext({}) // Find related documents const relatedDocs = await findRelatedDocuments(document) return { document, content_analysis: contentAnalysis, link_analysis: linkAnalysis, ai_context: aiContext, related_documents: relatedDocs, recommendations: generateDocumentRecommendations(document, contentAnalysis) } })
• src/tools/documents.ts:336-350 (schema)

  The MCPTool definition including input schema for validating the document_id parameter (UUID string).
  export const getDocumentContextTool: MCPTool = { name: 'get_document_context', description: 'Get document with full context including links, references, and AI metadata', inputSchema: { type: 'object', properties: { document_id: { type: 'string', format: 'uuid', description: 'The unique identifier of the document' } }, required: ['document_id'] } }
• src/tools/documents.ts:1346-1358 (registration)

  Registration of the getDocumentContext handler in the documentHandlers object, likely used to register all document-related handlers centrally.
  export const documentHandlers = { list_documents: listDocuments, create_document: createDocument, get_document: getDocument, update_document: updateDocument, search_documents: searchDocuments, get_document_context: getDocumentContext, add_document_collaborator: addDocumentCollaborator, analyze_document_content: analyzeDocumentContent, get_document_collaboration: getDocumentCollaboration, generate_document_template: generateDocumentTemplate, bulk_document_operations: bulkDocumentOperations }
• src/tools/documents.ts:1361-1373 (registration)

  Export/registration of the getDocumentContextTool in the documentTools object for MCP tool registration.
  export const documentTools = { listDocumentsTool, createDocumentTool, getDocumentTool, updateDocumentTool, searchDocumentsTool, getDocumentContextTool, addDocumentCollaboratorTool, analyzeDocumentContentTool, getDocumentCollaborationTool, generateDocumentTemplateTool, bulkDocumentOperationsTool }
• src/tools/documents.ts:378-407 (helper)

  Key helper function called by the handler to analyze document content, extracting metrics like word count, headings, links, complexity, and AI readiness score.
  function analyzeDocumentContentHelper(content: string, documentType: string): object { // Parse frontmatter if present const frontmatterMatch = content.match(/^---\n([\s\S]*?)\n---/) const hasFrontmatter = !!frontmatterMatch // Extract plain content (without frontmatter) const plainContent = hasFrontmatter ? content.replace(/^---\n[\s\S]*?\n---\n/, '') : content // Basic content analysis const words = plainContent.split(/\s+/).filter(w => w.length > 0) const lines = plainContent.split('\n') const headings = (plainContent.match(/^#+\s+.+$/gm) || []).length const codeBlocks = (plainContent.match(/```[\s\S]*?```/g) || []).length const links = (plainContent.match(/\[([^\]]+)\]\([^)]+\)/g) || []).length const internalLinks = (plainContent.match(/\[\[([^\]]+)\]\]/g) || []).length return { word_count: words.length, line_count: lines.length, character_count: plainContent.length, heading_count: headings, code_block_count: codeBlocks, link_count: links, internal_link_count: internalLinks, has_frontmatter: hasFrontmatter, estimated_read_time: Math.ceil(words.length / 200), // 200 words per minute content_complexity: calculateContentComplexity(plainContent, documentType), ai_readiness_score: calculateAIReadinessScore(content, hasFrontmatter) } }