feat(mcp): add mindbase_draft retrieval-pack tool

apps/mcp-server/tool-dispatcher.ts

@@ -40,6 +40,9 @@ export function createDispatcher(
     content_generate: (args) => tools.contentGenerate(args),
     content_publish: (args) => tools.contentPublish(args),
 
+    // Retrieval pack
+    mindbase_draft: (args) => tools.mindbaseDraft(args),
+
     // Memory
     memory_write: (args) => memoryTools.memoryWrite(args),
     memory_read: (args) => memoryTools.memoryRead(args),

apps/mcp-server/tool-registry.ts

@@ -421,6 +421,55 @@ const CONTENT_TOOLS: Tool[] = [
   },
 ];
 
+// Retrieval tools (context packs — no LLM calls)
+const RETRIEVAL_TOOLS: Tool[] = [
+  {
+    name: 'mindbase_draft',
+    description:
+      'Assemble a structured context pack from past conversations for writing an article/post — returns sources, chronological excerpts, a platform frontmatter skeleton, and writing notes; the caller writes the content. Provide exactly one of "topic" (semantic search) or "conversationIds" (explicit selection).',
+    inputSchema: {
+      type: 'object',
+      properties: {
+        topic: {
+          type: 'string',
+          description: 'Semantic search query for relevant past conversations (exactly one of topic/conversationIds required)',
+        },
+        conversationIds: {
+          type: 'array',
+          items: { type: 'string' },
+          description: 'Explicit conversation IDs to include (exactly one of topic/conversationIds required)',
+        },
+        project: {
+          type: 'string',
+          description: 'Filter search results by project (only valid with topic)',
+        },
+        source: {
+          type: 'string',
+          enum: ['claude-code', 'claude-desktop', 'chatgpt', 'cursor', 'windsurf', 'gemini'],
+          description: 'Filter search results by source platform (only valid with topic)',
+        },
+        limit: {
+          type: 'number',
+          description: 'Maximum number of conversations to include (default: 8, max: 20)',
+        },
+        platform: {
+          type: 'string',
+          enum: ['zenn', 'qiita', 'note', 'blog'],
+          description: 'Target platform for the frontmatter skeleton and writing notes (default: "blog")',
+        },
+        maxExcerptChars: {
+          type: 'number',
+          description: 'Maximum characters per conversation excerpt (default: 1200)',
+        },
+        maxTotalChars: {
+          type: 'number',
+          description: 'Total character budget across all excerpts (default: 24000)',
+        },
+      },
+    },
+  },
+];
+
 // Memory tools
 const MEMORY_TOOLS: Tool[] = [
   {
@@ -555,5 +604,6 @@ export const TOOLS: Tool[] = [
   ...SESSION_TOOLS,
   ...CROSS_SOURCE_TOOLS,
   ...CONTENT_TOOLS,
+  ...RETRIEVAL_TOOLS,
   ...MEMORY_TOOLS,
 ];

apps/mcp-server/tools/conversation.ts

@@ -5,22 +5,26 @@
  * - SessionTools: session management
  * - SearchTools: semantic and hybrid search
  * - ContentTools: article generation and publishing
+ * - RetrievalTools: retrieval-pack assembly (no LLM calls)
  */
 
 import type { StorageBackend, ConversationItem, QueryFilters, TimelineOptions } from '../storage/interface.js';
 import { SessionTools } from './session-tools.js';
 import { SearchTools } from './search-tools.js';
 import { ContentTools } from './content-tools.js';
+import { RetrievalTools } from './retrieval-tools.js';
 
 export class ConversationTools {
   private sessionTools: SessionTools;
   private searchTools: SearchTools;
   private contentTools: ContentTools;
+  private retrievalTools: RetrievalTools;
 
   constructor(private storage: StorageBackend) {
     this.sessionTools = new SessionTools(storage);
     this.searchTools = new SearchTools(storage, this.formatItem);
     this.contentTools = new ContentTools(storage);
+    this.retrievalTools = new RetrievalTools(storage);
   }
 
   setCurrentSession(sessionId: string | undefined) {
@@ -116,6 +120,9 @@ export class ConversationTools {
   contentGenerate = (...a: Parameters<ContentTools['contentGenerate']>) => this.contentTools.contentGenerate(...a);
   contentPublish = (...a: Parameters<ContentTools['contentPublish']>) => this.contentTools.contentPublish(...a);
 
+  // --- Delegated: Retrieval ---
+  mindbaseDraft = (...a: Parameters<RetrievalTools['mindbaseDraft']>) => this.retrievalTools.mindbaseDraft(...a);
+
   // --- Cross-source ---
 
   async conversationTimeline(args: {

apps/mcp-server/tools/retrieval-tools.ts

@@ -0,0 +1,263 @@
+/**
+ * MindBase MCP Server - Retrieval Tools
+ *
+ * Retrieval-pack assembly for article writing. NO LLM calls — this only
+ * gathers, organizes, and budgets past conversations into a structured
+ * context pack. The calling agent writes the actual content.
+ */
+
+import type { StorageBackend, ConversationItem } from '../storage/interface.js';
+
+export type DraftPlatform = 'zenn' | 'qiita' | 'note' | 'blog';
+
+export interface MindbaseDraftArgs {
+  topic?: string;
+  conversationIds?: string[];
+  project?: string;
+  source?: string;
+  limit?: number;
+  platform?: DraftPlatform;
+  maxExcerptChars?: number;
+  maxTotalChars?: number;
+}
+
+export interface DraftSource {
+  id: string;
+  title: string;
+  source: string;
+  project?: string;
+  occurredAt: string;
+  similarity?: number;
+}
+
+export interface DraftExcerpt {
+  conversationId: string;
+  occurredAt: string;
+  text: string;
+  truncated: boolean;
+}
+
+export interface DraftCoverage {
+  found: number;
+  included: number;
+  truncatedCount: number;
+  droppedIds: string[];
+}
+
+export interface DraftPack {
+  frontmatterSkeleton: string;
+  writingNotes: string[];
+  sources: DraftSource[];
+  excerpts: DraftExcerpt[];
+  coverage: DraftCoverage;
+}
+
+const DEFAULT_LIMIT = 8;
+const MAX_LIMIT = 20;
+const DEFAULT_MAX_EXCERPT_CHARS = 1200;
+const DEFAULT_MAX_TOTAL_CHARS = 24000;
+/** Same threshold as content_generate's semantic search. */
+const SEARCH_THRESHOLD = 0.5;
+
+/**
+ * Frontmatter skeletons mirror the field sets used by the publishers in
+ * libs/generators/publishers/ (zenn-publisher.ts formatZennArticle,
+ * qiita-publisher.ts preview, note-publisher.ts preview). The publishers do
+ * not export their frontmatter builders, so the field sets are minimally
+ * duplicated here — keep them in sync with those files.
+ */
+const FRONTMATTER_SKELETONS: Record<DraftPlatform, string> = {
+  zenn: [
+    '---',
+    'title: "TODO: 記事タイトル（50文字以内、検索を意識した具体的な形）"',
+    'emoji: "📝"',
+    'type: "tech"',
+    'topics: ["TODO-topic1", "TODO-topic2"]',
+    'published: false',
+    '---',
+  ].join('\n'),
+  qiita: [
+    '---',
+    'title: "TODO: 「〇〇で△△する方法」形式のタイトル"',
+    'tags:',
+    '  - name: "TODO-tag1"',
+    '  - name: "TODO-tag2"',
+    'private: true',
+    '---',
+  ].join('\n'),
+  // note.com articles do not use YAML frontmatter (see note-publisher.ts
+  // preview and platform-prompts.ts NOTE_PROMPT): title heading + hashtags.
+  note: [
+    '# TODO: タイトル（30文字以内、好奇心を刺激する形）',
+    '',
+    '#TODOタグ1 #TODOタグ2',
+  ].join('\n'),
+  blog: [
+    '---',
+    'title: "TODO: article title"',
+    'date: "TODO: YYYY-MM-DD"',
+    'tags: ["TODO-tag1", "TODO-tag2"]',
+    'draft: true',
+    '---',
+  ].join('\n'),
+};
+
+/**
+ * Platform conventions distilled from libs/generators/platform-prompts.ts
+ * (source of truth for the full prompts).
+ */
+const WRITING_NOTES: Record<DraftPlatform, string[]> = {
+  zenn: [
+    '中〜上級エンジニア向けに正確で再現可能な手順を書く。環境情報（OS、言語バージョン等）を冒頭に明記する',
+    'Zenn独自記法（:::message, :::details, :::warning）と言語指定・コメント付きコードブロックを活用する',
+    '「問題 → 調査 → 解決 → 学び」の流れでまとめ、最後に要点を箇条書きにする',
+  ],
+  qiita: [
+    '冒頭に「TL;DR」で結論を先出しし、環境・前提条件セクションを必ず置く',
+    '手順は番号付きでコマンドはコピペ可能に。コードブロックにはファイル名を付ける',
+    'エラーメッセージとその解決策をセットで示し、「参考リンク」セクションで締める',
+  ],
+  note: [
+    '非エンジニア読者も想定し、専門用語は噛み砕いて「〜してみました」など柔らかい語尾で語りかける',
+    'パラグラフは3行以内・空行多め・コードブロックは最小限にし、個人的な体験や感想を織り交ぜる',
+    'リード文で「何が得られるか」を明示し、最後に「まとめ」と次のアクションを提示する',
+  ],
+  blog: [
+    '対象読者と記事から得られるものを冒頭で明示する',
+    '見出しで構造化し、コードブロックには言語指定を付ける',
+  ],
+};
+
+function toIso(value: Date | string): string {
+  return value instanceof Date ? value.toISOString() : new Date(value).toISOString();
+}
+
+function toTime(value: Date | string): number {
+  return value instanceof Date ? value.getTime() : new Date(value).getTime();
+}
+
+/**
+ * Extract full text from conversation content, following the same content
+ * shape handling as content-tools.ts (content.messages with role/content).
+ */
+function extractText(item: ConversationItem): string {
+  const rawMessages = item.content?.messages;
+  if (Array.isArray(rawMessages) && rawMessages.length > 0) {
+    return rawMessages
+      .filter((m: any) => m.role === 'user' || m.role === 'assistant')
+      .map((m: any) => `${m.role}: ${typeof m.content === 'string' ? m.content : JSON.stringify(m.content)}`)
+      .join('\n');
+  }
+  return typeof item.content === 'string' ? item.content : JSON.stringify(item.content ?? '');
+}
+
+export class RetrievalTools {
+  constructor(private storage: StorageBackend) {}
+
+  async mindbaseDraft(args: MindbaseDraftArgs): Promise<DraftPack> {
+    const hasTopic = typeof args.topic === 'string' && args.topic.trim().length > 0;
+    const hasIds = Array.isArray(args.conversationIds) && args.conversationIds.length > 0;
+    if (hasTopic === hasIds) {
+      throw new Error('Exactly one of "topic" or "conversationIds" is required');
+    }
+    if (hasIds && (args.project || args.source)) {
+      throw new Error('"project" and "source" filters are only valid with "topic"');
+    }
+
+    const limit = Math.min(Math.max(args.limit ?? DEFAULT_LIMIT, 1), MAX_LIMIT);
+    const platform = args.platform ?? 'blog';
+    if (!(platform in FRONTMATTER_SKELETONS)) {
+      throw new Error(`Unknown platform: ${platform}. Supported: ${Object.keys(FRONTMATTER_SKELETONS).join(', ')}`);
+    }
+    const maxExcerptChars = args.maxExcerptChars ?? DEFAULT_MAX_EXCERPT_CHARS;
+    const maxTotalChars = args.maxTotalChars ?? DEFAULT_MAX_TOTAL_CHARS;
+
+    const droppedIds: string[] = [];
+    let selected: Array<{ item: ConversationItem; similarity?: number }> = [];
+    let found = 0;
+
+    if (hasIds) {
+      for (const id of args.conversationIds!) {
+        const item = await this.storage.getById(id);
+        if (item) {
+          selected.push({ item });
+        } else {
+          // Requested but not found — surface instead of silently skipping.
+          droppedIds.push(id);
+        }
+      }
+      found = selected.length;
+    } else {
+      // Over-fetch when post-hoc filters apply (semanticSearch has no
+      // project/source filters), so filtering does not starve the result set.
+      const fetchLimit = args.project || args.source ? Math.min(limit * 3, 60) : limit;
+      const results = await this.storage.semanticSearch(args.topic!, fetchLimit, SEARCH_THRESHOLD);
+
+      let filtered = results;
+      if (args.source) {
+        filtered = filtered.filter((r) => r.item.source === args.source);
+      }
+      if (args.project) {
+        filtered = filtered.filter((r) => r.item.metadata?.project === args.project);
+      }
+      found = filtered.length;
+      selected = filtered.map((r) => ({ item: r.item, similarity: r.similarity }));
+    }
+
+    // Enforce limit visibly: anything beyond it goes to droppedIds.
+    if (selected.length > limit) {
+      for (const extra of selected.slice(limit)) {
+        droppedIds.push(extra.item.id);
+      }
+      selected = selected.slice(0, limit);
+    }
+
+    // Chronological order (oldest first). The schema has no separate
+    // occurred_at column; created_at is the conversation's occurrence time.
+    selected.sort((a, b) => toTime(a.item.createdAt) - toTime(b.item.createdAt));
+
+    const sources: DraftSource[] = [];
+    const excerpts: DraftExcerpt[] = [];
+    let truncatedCount = 0;
+    let remaining = maxTotalChars;
+
+    for (const { item, similarity } of selected) {
+      if (remaining <= 0) {
+        // Total budget exhausted — drop visibly.
+        droppedIds.push(item.id);
+        continue;
+      }
+
+      const fullText = extractText(item);
+      const cap = Math.min(maxExcerptChars, remaining);
+      const truncated = fullText.length > cap;
+      const text = truncated ? fullText.slice(0, cap) : fullText;
+      remaining -= text.length;
+      if (truncated) truncatedCount++;
+
+      const occurredAt = toIso(item.createdAt);
+      sources.push({
+        id: item.id,
+        title: item.title,
+        source: item.source,
+        project: item.metadata?.project,
+        occurredAt,
+        similarity,
+      });
+      excerpts.push({ conversationId: item.id, occurredAt, text, truncated });
+    }
+
+    return {
+      frontmatterSkeleton: FRONTMATTER_SKELETONS[platform],
+      writingNotes: WRITING_NOTES[platform],
+      sources,
+      excerpts,
+      coverage: {
+        found,
+        included: excerpts.length,
+        truncatedCount,
+        droppedIds,
+      },
+    };
+  }
+}