export declare const mcpToolsTemplate = "import fs from \"node:fs\";\nimport path from \"node:path\";\nimport type {\n  MCPToolDefinition,\n  DocsResource,\n  DocsChunk,\n  GetDocParams,\n  ListDocsParams,\n} from \"@/services/mcp/types\";\n\n// Keep the corpus out of the function's JavaScript bundle. next.config.ts\n// traces this fixed file into the RAG/MCP functions, just like docs-index.json.\nconst DOCS_CONTENT_FILE = path.join(\n  process.cwd(),\n  \"services\",\n  \"mcp\",\n  \"docs-content.json\",\n);\n\nlet docsContentCache:\n  { mtimeMs: number; size: number; docs: DocsResource[] } | undefined;\n\nfunction loadDocsContent(): DocsResource[] {\n  try {\n    // Generated content changes while `next dev` stays alive. Key the cache by\n    // file metadata so watch-mode updates become visible without parsing the\n    // whole corpus on every tool call.\n    const stat = fs.statSync(DOCS_CONTENT_FILE);\n    if (\n      docsContentCache?.mtimeMs === stat.mtimeMs &&\n      docsContentCache.size === stat.size\n    ) {\n      return docsContentCache.docs;\n    }\n    const parsed: unknown = JSON.parse(\n      fs.readFileSync(DOCS_CONTENT_FILE, \"utf8\"),\n    );\n    const docs = Array.isArray(parsed) ? (parsed as DocsResource[]) : [];\n    docsContentCache = { mtimeMs: stat.mtimeMs, size: stat.size, docs };\n    return docs;\n  } catch {\n    docsContentCache = undefined;\n    return [];\n  }\n}\n\n/**\n * Tool definitions for MCP - these describe the available tools\n */\nexport const DOCS_TOOLS: MCPToolDefinition[] = [\n  {\n    name: \"search_docs\",\n    description:\n      \"Search through the documentation content using semantic search. Returns relevant chunks of documentation based on the query.\",\n    inputSchema: {\n      type: \"object\",\n      properties: {\n        query: {\n          type: \"string\",\n          description: \"The search query to find relevant documentation\",\n        },\n        limit: {\n          type: \"number\",\n          description: \"Maximum number of results to return (default: 6)\",\n        },\n      },\n      required: [\"query\"],\n    },\n  },\n  {\n    name: \"get_doc\",\n    description:\n      \"Get the full content of a specific documentation page by its path.\",\n    inputSchema: {\n      type: \"object\",\n      properties: {\n        path: {\n          type: \"string\",\n          description:\n            \"The file path to the documentation page (e.g., 'app/getting-started/page.tsx')\",\n        },\n      },\n      required: [\"path\"],\n    },\n  },\n  {\n    name: \"list_docs\",\n    description:\n      \"List all available documentation pages, optionally filtered by directory.\",\n    inputSchema: {\n      type: \"object\",\n      properties: {\n        directory: {\n          type: \"string\",\n          description:\n            \"Optional directory to filter results (e.g., 'components')\",\n        },\n      },\n    },\n  },\n];\n\n/**\n * List all documentation resources\n */\nexport async function listDocs(\n  params?: ListDocsParams,\n): Promise<DocsResource[]> {\n  const docsContent = loadDocsContent();\n  const filterDir = params?.directory?.replace(/\\\\/g, \"/\");\n  const resources = filterDir\n    ? docsContent.filter((doc) => doc.path.includes(filterDir))\n    : docsContent;\n  return resources.map((doc) => ({ ...doc }));\n}\n\n/**\n * Get a specific documentation page\n */\nexport async function getDoc(\n  params: GetDocParams,\n): Promise<DocsResource | null> {\n  const docsContent = loadDocsContent();\n  const requested = params.path.trim().replace(/\\\\/g, \"/\");\n  if (!requested || requested.includes(\"\\0\")) return null;\n\n  const withoutScheme = requested.replace(/^docs:\\/\\//, \"\");\n  const route = withoutScheme\n    .replace(/^app\\/(?:\\([^/]+\\)\\/)?/, \"\")\n    .replace(/(?:^|\\/)page\\.(?:tsx?|jsx?)$/, \"\")\n    .replace(/^\\/+|\\/+$/g, \"\");\n\n  const doc = docsContent.find((candidate) => {\n    const candidateRoute = candidate.uri\n      .replace(/^docs:\\/\\//, \"\")\n      .replace(/^\\/+|\\/+$/g, \"\");\n    return (\n      candidate.path === requested ||\n      candidate.uri === requested ||\n      candidateRoute === route\n    );\n  });\n\n  return doc ? { ...doc } : null;\n}\n\n/**\n * Chunk text for embeddings.\n * - chunkSize=800 chars balances granularity with embedding context window limits\n * - overlap=100 chars ensures continuity so searches don't miss content at chunk boundaries\n */\nfunction chunkText(text: string, chunkSize = 800, overlap = 100): string[] {\n  const chunks: string[] = [];\n  let i = 0;\n  while (i < text.length) {\n    const end = Math.min(i + chunkSize, text.length);\n    chunks.push(text.slice(i, end));\n    if (end === text.length) break;\n    i = end - overlap;\n    if (i < 0) i = 0;\n  }\n  return chunks;\n}\n\n/**\n * Get all documentation chunks for indexing\n */\nexport async function getAllDocsChunks(): Promise<DocsChunk[]> {\n  const allChunks: DocsChunk[] = [];\n  const docs = await listDocs();\n\n  for (const doc of docs) {\n    const cleanContent = doc.content\n      .replace(/\\r\\n/g, \"\\n\")\n      .replace(/\\n{3,}/g, \"\\n\\n\")\n      .slice(0, 200_000);\n\n    const textChunks = chunkText(cleanContent);\n    for (let i = 0; i < textChunks.length; i++) {\n      allChunks.push({\n        id: `${doc.path}:${i}`,\n        text: textChunks[i],\n        path: doc.path,\n        uri: doc.uri,\n      });\n    }\n  }\n\n  return allChunks;\n}\n";