Yandex Cloud

This Yandex Cloud MCP server acts as a friendly bridge between the Claude AI desktop app and Yandex Cloud’s storage system. In simple terms, it gives the AI the ability to "look" inside cloud storage folders and manage files directly through a chat interface. Instead of a user having to manually download data and upload it to the AI, they can simply ask the assistant to browse their cloud buckets or fetch specific documents, making cloud management feel like a natural conversation. On a more technical level, the tool provides three essential capabilities: listing all buckets in an account, viewing the contents of a specific bucket, and downloading files to a local directory. It uses the Model Context Protocol to expose these functions as tools that a Large Language Model can call upon autonomously. This allows the AI to perform complex operations, such as scanning large datasets for specific information or preparing local environments with cloud-hosted assets, all based on simple natural language prompts. The server is built using Node.js and TypeScript, leveraging the AWS SDK’s compatibility with Yandex Cloud’s S3-compliant endpoints. Security is a priority, as the system manages authentication through environment variables and service account keys to ensure sensitive credentials remain protected. For developers building AI-driven workflows, this MCP server is an invaluable asset because it turns static cloud storage into an active, queryable resource that an AI agent can navigate and utilize to provide deeper, data-driven insights.

Category: Cloud & Infrastructure

Tags: cloud-storage, object-storage, s3, yandex-cloud

Visit Yandex Cloud

How to install and configure Yandex Cloud

1. Installation To set up the Yandex Cloud MCP server locally, follow these steps: Step 1: Create the project directory bash mkdir yandex-cloud-mcp cd yandex-cloud-mcp npm init -y Step 2: Install dependencies bash # Main dependencies npm install @modelcontextprotocol/sdk @aws-sdk/client-s3 dotenv # Development dependencies npm install -D typescript @types/node ts-node nodemon Step 3: Configure TypeScript Create a tsconfig.json file in the root directory: json { "compilerOptions": { "target": "ES2020", "module": "commonjs", "outDir": "./dist", "rootDir": "./src", "strict": true, "esModuleInterop": true, "skipLibCheck": true, "forceConsistentCasingInFileNames": true, "resolveJsonModule": true }, "include": ["src/**/*"], "exclude": ["node_modules", "dist"] } Step 4: Update package.json scripts Add the following to your package.json: json "scripts": { "build": "tsc", "start": "node dist/index.js", "dev": "ts-node src/index.ts", "watch": "nodemon --exec ts-node src/index.ts" } Step 5: Create source and build 1. Create a src folder. 2. Create src/index.ts and paste the server code (starting with #!/usr/bin/env node). 3. Build the project: bash npm run build ---

2. Configuration

Yandex Cloud Credentials You must obtain a Static Access Key from the Yandex Cloud Console: 1. Create a Service Account in IAM. 2. Assign roles: storage.editor (read/write) or storage.viewer (read-only). 3. Create a Static Access Key and save the Access Key ID and Secret Access Key.

Claude Desktop Configuration Add the server to your claude_desktop_config.json file: - Windows: %APPDATA%\Claude\claude_desktop_config.json - macOS: ~/Library/Application Support/Claude/claude_desktop_config.json JSON Configuration: json { "mcpServers": { "yandex-cloud": { "command": "node", "args": ["/FULL/PATH/TO/YOUR/PROJECT/yandex-cloud-mcp/dist/index.js"], "env": { "YANDEX_ACCESS_KEY_ID": "YOUR_ACCESS_KEY_ID", "YANDEX_SECRET_ACCESS_KEY": "YOUR_SECRET_ACCESS_KEY" } } } } Note: Replace /FULL/PATH/TO/YOUR/PROJECT/ with the actual absolute path to your project folder. ---

3. Available Tools The server provides tools to interact with Yandex Object Storage (S3-compatible API): | Tool | Description | | :--- | :--- | | List Buckets | Displays a list of all buckets in your Yandex Cloud account. | | View Content | Browse the files and folders within a specific bucket. | | Download Files | Download files from a bucket to a local directory. | ---

4. Example Prompts Once configured, you can use prompts like these in Claude: * "Можешь показать мои bucket в Yandex Cloud?" (Can you show my buckets in Yandex Cloud?) * "What files are inside my [bucket-name] bucket?" * "Download the latest log file from Yandex Cloud storage."

What you can do with Yandex Cloud

Use Case 1: Automated Log Analysis and Troubleshooting Problem: DevOps engineers and developers often store application logs in Yandex Cloud Object Storage. When a production issue occurs, manually finding, downloading, and searching through these large log files to identify errors is time-consuming and tedious. Solution: This MCP allows Claude to directly interact with your Yandex Cloud buckets. You can ask Claude to find the most recent log file, download it, and analyze the content for specific stack traces or error patterns without ever leaving the chat interface. Example: "Claude, list the contents of the production-logs bucket. Find the log file from the last hour, download it, and tell me if there are any '500 Internal Server Error' entries."

Use Case 2: Content Audit and Storage Organization Problem: Over time, Object Storage buckets can become cluttered with temporary files, old backups, or inconsistently named assets. Getting a high-level overview or "audit" of what is taking up space usually requires navigating through the web console or writing custom scripts. Solution: Claude can use the MCP to list all objects in a bucket and categorize them. It can help identify large files, old versions, or files that don't follow naming conventions, providing a clear summary and suggestions for cleanup. Example: "List all files in my marketing-assets bucket. Group them by file type and tell me which files are older than six months so I can decide what to archive."

Use Case 3: Seamless Integration for AI-Assisted Research Problem: Researchers and data scientists often store datasets, PDFs, or research papers in cloud buckets. When they want to ask an AI questions based on those specific documents, they have to manually download the file from the cloud and then upload it back into the AI's chat window. Solution: This MCP bridges the gap between the storage and the AI. Claude can browse the bucket, identify the relevant document the user is talking about, download it to the local environment, and then use its reasoning capabilities to answer questions or summarize the data. Example: "Look into my project-research bucket and find the PDF about 'Q3 Market Trends'. Download it and give me a 5-bullet point summary of the main findings."

Use Case 4: Verifying CI

CD Build Artifacts Problem: After a CI/CD pipeline runs, a developer needs to verify that the build artifacts (like a .zip or .apk file) were correctly generated and…

Key facts

• Open Source
• Cloud & Infrastructure, Files, Documents & PDFs
• cloud-storage, object-storage, s3, yandex-cloud

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