Outline Wiki MCP Server

Instructions

Implementation Reference

• src/lib/handlers/smart.ts:22-83 (handler)

  The core handler function that implements the sync_knowledge tool logic: fetches documents from Outline API, retrieves full text content, and synchronizes them to the vector store (brain) for RAG capabilities.
  async sync_knowledge(args: { collectionId?: string }) { if (!brain.isEnabled()) { return { error: ERROR_MESSAGES.SMART_FEATURES_DISABLED }; } // Step 1: Fetch document list from Outline const payload: Record<string, unknown> = { limit: 100 }; if (args.collectionId) { payload.collectionId = args.collectionId; } const { data: docList } = await apiCall(() => apiClient.post<OutlineDocument[]>('/documents.list', payload) ); if (!docList || docList.length === 0) { return { message: ERROR_MESSAGES.NO_DOCUMENTS_FOUND, synced: 0 }; } // Step 2: Fetch full content for each document (list API may truncate text) const wikiDocs: WikiDocument[] = []; let fetchErrors = 0; for (const doc of docList) { try { const { data: fullDoc } = await apiCall(() => apiClient.post<OutlineDocument>('/documents.info', { id: doc.id }) ); if (fullDoc && fullDoc.text) { wikiDocs.push({ id: fullDoc.id, title: fullDoc.title, text: fullDoc.text, url: `${baseUrl}${fullDoc.url}`, collectionId: fullDoc.collectionId, }); } } catch { fetchErrors++; } } if (wikiDocs.length === 0) { return { message: ERROR_MESSAGES.NO_DOCUMENTS_WITH_CONTENT, synced: 0, errors: fetchErrors, }; } // Step 3: Sync to brain (vectorize) const result = await brain.syncDocuments(wikiDocs); return { message: `Successfully synced ${result.documents} documents (${result.chunks} chunks).`, documents: result.documents, chunks: result.chunks, skipped: docList.length - wikiDocs.length, errors: fetchErrors, }; },
• src/lib/schemas.ts:142-144 (schema)

  Zod schema definition for the sync_knowledge tool input, which accepts an optional collectionId.
  export const syncKnowledgeSchema = z.object({ collectionId: collectionId.optional(), });
• src/lib/tools.ts:200-204 (registration)

  Registers the sync_knowledge tool in the allTools array, providing name, description, and schema reference for MCP tool definition.
  createTool( 'sync_knowledge', 'Sync documents to vector store for AI-powered search. Run this before using ask_wiki.', 'sync_knowledge' ),
• src/lib/schemas.ts:200-200 (schema)

  TypeScript type derived from the syncKnowledgeSchema for input validation.
  export type SyncKnowledgeInput = z.infer<typeof syncKnowledgeSchema>;
• src/lib/schemas.ts:244-244 (schema)

  Includes the sync_knowledge schema in the central toolSchemas map used by tool definitions.
  sync_knowledge: syncKnowledgeSchema,