Linting

Author: cmsparks

apps/docs-autorag/README.md

@@ -18,4 +18,4 @@ Then connect to the server via remote MCP at `http://localhost:8976/sse`
 
 ```
 pnpm run deploy --env [ENVIRONMENT]
-```
+```

apps/docs-autorag/src/index.ts

@@ -1,5 +1,6 @@
 import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js'
 import { McpAgent } from 'agents/mcp'
+
 import { registerDocsTools } from './tools/docs'
 
 // The docs MCP server isn't stateful, so we don't have state/props
@@ -13,7 +14,10 @@ export class CloudflareDocumentationMCP extends McpAgent<Env, State, Props> {
 		version: '1.0.0',
 	})
 
-	constructor(public ctx: DurableObjectState, public env: Env) {
+	constructor(
+		public ctx: DurableObjectState,
+		public env: Env
+	) {
 		super(ctx, env)
 	}
 

apps/docs-autorag/src/tools/docs.ts

@@ -1,7 +1,9 @@
+import { type EmbeddedResource } from '@modelcontextprotocol/sdk/types.js'
+import mime from 'mime'
 import { z } from 'zod'
+
 import type { CloudflareDocumentationMCP } from '../index'
-import { type EmbeddedResource } from "@modelcontextprotocol/sdk/types.js"
-import mime from "mime"
+
 /**
  * Registers the docs search tool with the MCP server
  * @param agent The MCP server instance
@@ -18,7 +20,7 @@ export function registerDocsTools(agent: CloudflareDocumentationMCP) {
 		- You are unsure of how to use some Cloudflare functionality
 		- You are writing Cloudflare Workers code and need to look up Workers-specific documentation
 
-		This tool returns a number of results from a vector database. These are embedded as resources in the response and are plaintext doucments in a variety of formats.
+		This tool returns a number of results from a vector database. These are embedded as resources in the response and are plaintext documents in a variety of formats.
 		`,
 		{
 			// partially pulled from autorag query optimization example
@@ -28,35 +30,46 @@ export function registerDocsTools(agent: CloudflareDocumentationMCP) {
 3. Remove irrelevant filler words
 4. Structure the query to emphasize key terms
 5. Include technical or domain-specific terminology if applicable`),
-			scoreThreshold: z.number().min(0).max(1).optional().describe("A score threshold (0-1) for which matches should be included."),
-			maxNumResults: z.number().default(10).optional().describe("The maximum number of results to return.")
+			scoreThreshold: z
+				.number()
+				.min(0)
+				.max(1)
+				.optional()
+				.describe('A score threshold (0-1) for which matches should be included.'),
+			maxNumResults: z
+				.number()
+				.default(10)
+				.optional()
+				.describe('The maximum number of results to return.'),
 		},
 		async (params) => {
 			// we don't need "rewrite query" OR aiSearch because an LLM writes the query and formats the output for us.
 			const result = await agent.env.AI.autorag(agent.env.AUTORAG_NAME).search({
 				query: params.query,
-				ranking_options: params.scoreThreshold ? {
-					score_threshold: params.scoreThreshold
-				} : undefined,
-				max_num_results: params.maxNumResults
+				ranking_options: params.scoreThreshold
+					? {
+							score_threshold: params.scoreThreshold,
+						}
+					: undefined,
+				max_num_results: params.maxNumResults,
 			})
 
 			const resources: EmbeddedResource[] = result.data.map((result) => {
 				const content = result.content.reduce((acc, contentPart) => {
 					return acc + contentPart.text
-				}, "")
+				}, '')
 				return {
-					type: "resource",
+					type: 'resource',
 					resource: {
 						uri: `docs://${result.filename}`,
-						mimeType: mime.getType(result.filename) ?? "text/plain",
-						text: content
-					}
+						mimeType: mime.getType(result.filename) ?? 'text/plain',
+						text: content,
+					},
 				}
 			})
 
 			return {
-				content: resources
+				content: resources,
 			}
 		}
 	)

apps/docs-autorag/tsconfig.json

@@ -1,4 +1,4 @@
 {
 	"extends": "@repo/typescript-config/workers.json",
-	"include": ["*/**.ts", "./vitest.config.ts"],
+	"include": ["*/**.ts", "./vitest.config.ts"]
 }

apps/docs-autorag/types.d.ts

@@ -30,7 +30,7 @@
 	},
 	"vars": {
 		"ENVIRONMENT": "development",
-		"AUTORAG_NAME": "cloudflare-docs-autorag",
+		"AUTORAG_NAME": "cloudflare-docs-autorag"
 	},
 	"dev": {
 		"port": 8976
@@ -52,7 +52,7 @@
 			},
 			"vars": {
 				"ENVIRONMENT": "staging",
-				"AUTORAG_NAME": "cloudflare-docs-autorag",
+				"AUTORAG_NAME": "cloudflare-docs-autorag"
 			},
 
 			"ai": {
@@ -73,7 +73,7 @@
 			},
 			"vars": {
 				"ENVIRONMENT": "production",
-				"AUTORAG_NAME": "cloudflare-docs-autorag",
+				"AUTORAG_NAME": "cloudflare-docs-autorag"
 			},
 			"ai": {
 				"binding": "AI"

apps/docs-autorag/wrangler.jsonc

@@ -1,5 +1,3 @@
-import { z } from 'zod'
-
 import { getCloudflareClient } from '../cloudflare-api'
 import { MISSING_ACCOUNT_ID_RESPONSE } from '../constants'
 import { type CloudflareMcpAgent } from '../types/cloudflare-mcp-agent'