Merge pull request #180 from Skirano/aws-kb-retrieval

added aws kb server

README.md

@@ -10,18 +10,21 @@ Each MCP server is implemented with either the [Typescript MCP SDK](https://gith
 
 These servers aim to demonstrate MCP features and the Typescript and Python SDK.
 
+- **[AWS KB Retrieval](src/aws-kb-retrieval)** - Retrieval from AWS Knowledge Base using Bedrock Agent Runtime
 - **[Brave Search](src/brave-search)** - Web and local search using Brave's Search API
+- **[EverArt](src/everart)** - AI image generation using various models
 - **[Fetch](src/fetch)** - Web content fetching and conversion for efficient LLM usage
 - **[Filesystem](src/filesystem)** - Secure file operations with configurable access controls
+- **[Git](src/git)** - Tools to read, search, and manipulate Git repositories
 - **[GitHub](src/github)** - Repository management, file operations, and GitHub API integration
 - **[GitLab](src/gitlab)** - GitLab API, enabling project management
-- **[Git](src/git)** - Tools to read, search, and manipulate Git repositories
 - **[Google Drive](src/gdrive)** - File access and search capabilities for Google Drive
 - **[Google Maps](src/google-maps)** - Location services, directions, and place details
 - **[Memory](src/memory)** - Knowledge graph-based persistent memory system
 - **[PostgreSQL](src/postgres)** - Read-only database access with schema inspection
 - **[Puppeteer](src/puppeteer)** - Browser automation and web scraping
 - **[Sentry](src/sentry)** - Retrieving and analyzing issues from Sentry.io
+- **[Sequential Thinking](src/sequential-thinking)** - Dynamic and reflective problem-solving through thought sequences
 - **[Slack](src/slack)** - Channel management and messaging capabilities
 - **[Sqlite](src/sqlite)** - Database interaction and business intelligence capabilities
 

src/aws-kb-retrieval-server/README.md

@@ -0,0 +1,53 @@
+# AWS Knowledge Base Retrieval MCP Server
+
+An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.
+
+## Features
+
+- **RAG (Retrieval-Augmented Generation)**: Retrieve context from the AWS Knowledge Base based on a query and a Knowledge Base ID.
+- **Supports multiple results retrieval**: Option to retrieve a customizable number of results.
+
+## Tools
+
+- **retrieve_from_aws_kb**
+  - Perform retrieval operations using the AWS Knowledge Base.
+  - Inputs:
+    - `query` (string): The search query for retrieval.
+    - `knowledgeBaseId` (string): The ID of the AWS Knowledge Base.
+    - `n` (number, optional): Number of results to retrieve (default: 3).
+
+## Configuration
+
+### Setting up AWS Credentials
+
+1. Obtain AWS access key ID, secret access key, and region from the AWS Management Console.
+2. Ensure these credentials have appropriate permissions for Bedrock Agent Runtime operations.
+
+### Usage with Claude Desktop
+
+Add this to your `claude_desktop_config.json`:
+
+```json
+{
+  "mcpServers": {
+    "aws-kb-retrieval": {
+      "command": "npx",
+      "args": [
+        "-y",
+        "@modelcontextprotocol/server-aws-kb-retrieval"
+      ],
+      "env": {
+        "AWS_ACCESS_KEY_ID": "YOUR_ACCESS_KEY_HERE",
+        "AWS_SECRET_ACCESS_KEY": "YOUR_SECRET_ACCESS_KEY_HERE",
+        "AWS_REGION": "YOUR_AWS_REGION_HERE"
+      }
+    }
+  }
+}
+```
+
+## License
+
+This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
+
+This README assumes that your server package is named `@modelcontextprotocol/server-aws-kb-retrieval`. Adjust the package name and installation details if they differ in your setup. Also, ensure that your server script is correctly built and that all dependencies are properly managed in your `package.json`.

src/aws-kb-retrieval-server/index.ts

@@ -0,0 +1,166 @@
+#!/usr/bin/env node
+import { Server } from "@modelcontextprotocol/sdk/server/index.js";
+import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
+import {
+  CallToolRequestSchema,
+  ListToolsRequestSchema,
+  Tool,
+} from "@modelcontextprotocol/sdk/types.js";
+import {
+  BedrockAgentRuntimeClient,
+  RetrieveCommand,
+  RetrieveCommandInput,
+} from "@aws-sdk/client-bedrock-agent-runtime";
+
+// AWS client initialization
+const bedrockClient = new BedrockAgentRuntimeClient({
+  region: process.env.AWS_REGION,
+  credentials: {
+    accessKeyId: process.env.AWS_ACCESS_KEY_ID!,
+    secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY!,
+  },
+});
+
+interface RAGSource {
+  id: string;
+  fileName: string;
+  snippet: string;
+  score: number;
+}
+
+async function retrieveContext(
+  query: string,
+  knowledgeBaseId: string,
+  n: number = 3
+): Promise<{
+  context: string;
+  isRagWorking: boolean;
+  ragSources: RAGSource[];
+}> {
+  try {
+    if (!knowledgeBaseId) {
+      console.error("knowledgeBaseId is not provided");
+      return {
+        context: "",
+        isRagWorking: false,
+        ragSources: [],
+      };
+    }
+
+    const input: RetrieveCommandInput = {
+      knowledgeBaseId: knowledgeBaseId,
+      retrievalQuery: { text: query },
+      retrievalConfiguration: {
+        vectorSearchConfiguration: { numberOfResults: n },
+      },
+    };
+
+    const command = new RetrieveCommand(input);
+    const response = await bedrockClient.send(command);
+    const rawResults = response?.retrievalResults || [];
+    const ragSources: RAGSource[] = rawResults
+      .filter((res) => res?.content?.text)
+      .map((result, index) => {
+        const uri = result?.location?.s3Location?.uri || "";
+        const fileName = uri.split("/").pop() || `Source-${index}.txt`;
+        return {
+          id: (result.metadata?.["x-amz-bedrock-kb-chunk-id"] as string) || `chunk-${index}`,
+          fileName: fileName.replace(/_/g, " ").replace(".txt", ""),
+          snippet: result.content?.text || "",
+          score: (result.score as number) || 0,
+        };
+      })
+      .slice(0, 3);
+
+    const context = rawResults
+      .filter((res): res is { content: { text: string } } => res?.content?.text !== undefined)
+      .map(res => res.content.text)
+      .join("\n\n");
+
+    return {
+      context,
+      isRagWorking: true,
+      ragSources,
+    };
+  } catch (error) {
+    console.error("RAG Error:", error);
+    return { context: "", isRagWorking: false, ragSources: [] };
+  }
+}
+
+// Define the retrieval tool
+const RETRIEVAL_TOOL: Tool = {
+  name: "retrieve_from_aws_kb",
+  description: "Performs retrieval from the AWS Knowledge Base using the provided query and Knowledge Base ID.",
+  inputSchema: {
+    type: "object",
+    properties: {
+      query: { type: "string", description: "The query to perform retrieval on" },
+      knowledgeBaseId: { type: "string", description: "The ID of the AWS Knowledge Base" },
+      n: { type: "number", default: 3, description: "Number of results to retrieve" },
+    },
+    required: ["query", "knowledgeBaseId"],
+  },
+};
+
+// Server setup
+const server = new Server(
+  {
+    name: "aws-kb-retrieval-server",
+    version: "0.2.0",
+  },
+  {
+    capabilities: {
+      tools: {},
+    },
+  },
+);
+
+// Request handlers
+server.setRequestHandler(ListToolsRequestSchema, async () => ({
+  tools: [RETRIEVAL_TOOL],
+}));
+
+server.setRequestHandler(CallToolRequestSchema, async (request) => {
+  const { name, arguments: args } = request.params;
+
+  if (name === "retrieve_from_aws_kb") {
+    const { query, knowledgeBaseId, n = 3 } = args as Record<string, any>;
+    try {
+      const result = await retrieveContext(query, knowledgeBaseId, n);
+      if (result.isRagWorking) {
+        return {
+          content: [
+            { type: "text", text: `Context: ${result.context}` },
+            { type: "text", text: `RAG Sources: ${JSON.stringify(result.ragSources)}` },
+          ],
+        };
+      } else {
+        return {
+          content: [{ type: "text", text: "Retrieval failed or returned no results." }],
+        };
+      }
+    } catch (error) {
+      return {
+        content: [{ type: "text", text: `Error occurred: ${error}` }],
+      };
+    }
+  } else {
+    return {
+      content: [{ type: "text", text: `Unknown tool: ${name}` }],
+      isError: true,
+    };
+  }
+});
+
+// Server startup
+async function runServer() {
+  const transport = new StdioServerTransport();
+  await server.connect(transport);
+  console.error("AWS KB Retrieval Server running on stdio");
+}
+
+runServer().catch((error) => {
+  console.error("Fatal error running server:", error);
+  process.exit(1);
+});

src/aws-kb-retrieval-server/package.json

@@ -0,0 +1,30 @@
+{
+  "name": "@modelcontextprotocol/server-aws-kb-retrieval",
+  "version": "0.6.2",
+  "description": "MCP server for AWS Knowledge Base retrieval using Bedrock Agent Runtime",
+  "license": "MIT",
+  "author": "Anthropic, PBC (https://anthropic.com)",
+  "homepage": "https://modelcontextprotocol.io",
+  "bugs": "https://github.com/modelcontextprotocol/servers/issues",
+  "type": "module",
+  "bin": {
+    "mcp-server-aws-kb-retrieval": "dist/index.js"
+  },
+  "files": [
+    "dist"
+  ],
+  "scripts": {
+    "build": "tsc && shx chmod +x dist/*.js",
+    "prepare": "npm run build",
+    "watch": "tsc --watch"
+  },
+  "dependencies": {
+    "@modelcontextprotocol/sdk": "0.5.0",
+    "@aws-sdk/client-bedrock-agent-runtime": "^3.0.0"
+  },
+  "devDependencies": {
+    "@types/node": "^20.10.0",
+    "shx": "^0.3.4",
+    "typescript": "^5.6.2"
+  }
+}

src/aws-kb-retrieval-server/tsconfig.json

@@ -0,0 +1,17 @@
+{
+  "extends": "../../tsconfig.json",
+  "compilerOptions": {
+    "outDir": "./dist",
+    "rootDir": ".",
+    "composite": true,
+    "incremental": true,
+    "tsBuildInfoFile": "./dist/.tsbuildinfo"
+  },
+  "include": [
+    "./**/*.ts"
+  ],
+  "exclude": [
+    "node_modules",
+    "dist"
+  ]
+}