base on The Intelligence Layer for AI agents. Connect your models, tools, and data to create agentic apps that can think, act and talk to you. <a href="https://dexto.ai"> <img src="https://raw.githubusercontent.com/truffle-ai/dexto/main/.github/assets/dexto-logo.svg" alt="Dexto" width="100%" style="max-width: 1000px" /> </a> <p align="center"> <img src="https://img.shields.io/badge/Status-Beta-yellow"> <img src="https://img.shields.io/badge/License-Elastic%202.0-blue.svg"> <a href="https://discord.gg/GFzWFAAZcm"><img src="https://img.shields.io/badge/Discord-Join%20Chat-7289da?logo=discord&logoColor=white"></a> <a href="https://deepwiki.com/truffle-ai/dexto"><img src="https://deepwiki.com/badge.svg"></a> </p> **An all-in-one toolkit to build agentic applications that turn natural language into real-world actions.** <div align="center"> <img src="https://github.com/user-attachments/assets/89d30349-0cb1-4160-85db-d99a80a71d7a" alt="Dexto Demo" width="700" /> </div> ## What is Dexto? Dexto is a universal intelligence layer for building collaborative, context-aware AI Agents & agentic apps. It orchestrates LLMs, tools, and data into persistent, stateful systems with memory, so you can rapidly create AI assistants, digital companions & copilots that think, act and feel alive. Dexto combines a configuration-driven framework, robust runtime, and seamless developer experience so you can build, deploy, and iterate on your agents easily. - **Framework** – Define agent behavior in YAML. Instantly swap models and tools without touching code. - **Runtime** – Execution with orchestration, session management, conversation memory, and multimodal support. - **Interfaces & Tooling** – Native support for CLI, Web, APIs, and a TypeScript SDK. #### With Dexto, you can build: - **Autonomous Agents** - Agents that plan, execute, and adapt to user goals. - **Digital Companions** - AI assistants & copilots that remember context and anticipate needs. - **MCP Clients** - Connect multiple tools, files, APIs, and data via MCP Servers. - **MCP Servers** - Dexto Web UI and MCP playground help you to easily test your own MCP servers. - **Multi-Agent Systems** - Architect agents that collaborate, delegate, and solve complex tasks together. - **Agent-as-a-Service** – Transform your existing SaaS products and APIs into dynamic, conversational experiences. - **Agentic Applications** – Integrate Dexto as a reasoning engine to power interactive, multimodal, AI-native applications. #### What You Get - **Batteries Included** – Session management, tool orchestration, multimodal support, and production-ready observability. - **50+ LLMs** – Instantly switch between OpenAI, Anthropic, Google, Groq, local models or bring your own. - **Run Anywhere** – Local for privacy, cloud for reach, or hybrid. *Same agent, any deployment.* - **Native Multimodal** – Text, images, files, and tools in a single conversation. *Upload screenshots, ask questions, take actions.* - **Persistent Sessions** – Conversations, context, and memory are saved and can be exported, imported, or shared across environments. - **Flexible Interfaces** – One agent, endless ways to interact: Ready-to-use CLI, WebUI, APIs, or integrate with your own UI. - **30+ Tools & MCP** – Integrate tools and connect to external servers via the Model Context Protocol (MCP) or use our internal tools. - **Pluggable Storage** – Use Redis, PostgreSQL, SQLite, in-memory, S3 and more for cache, database & blob backends. - **Human in the loop** - Configure approval policies for tool execution, agents can also remember which tools are safe per session. - **Observability** – Built-in OpenTelemetry distributed tracing, token usage monitoring, and error handling. --- ## Installation ```bash # NPM global npm install -g dexto # —or— build from source # this sets up dexto CLI from the cloned code git clone https://github.com/truffle-ai/dexto.git cd dexto && pnpm install && pnpm install-cli ``` ## Quick Start ```bash # 1. Run setup workflow - this prompts for your preferred LLM and API keys and opens the Web UI dexto # 2. Try a multi-step task in the web UI: "create a snake game in HTML/CSS/JS, then open it in the browser" # 3. Start interactive CLI mode instead of web UI dexto --mode cli ``` In 2 -> Dexto will use filesystem tools to write code and browser tools to open it — all from a single prompt. The Web UI (default mode) allows you to navigate previous conversations and experiment with different models, tools and more. The interactive CLI (3) allows you to interact with agents in the terminal. See the [CLI Guide](https://docs.dexto.ai/docs/guides/cli/overview) for full details. ### Skip Tool Prompts While Prototyping ```bash dexto --auto-approve "refactor my project using the filesystem and browser tools" ``` Use the `--auto-approve` flag to bypass confirmation prompts when you trust the tools being invoked—perfect for fast local iteration. Remove the flag when you want explicit approval again. ### Logs Logs are stored in `~/.dexto/logs` directory by default. Use `DEXTO_LOG_TO_CONSOLE=true` to log to console when running dexto. Use `DEXTO_LOG_LEVEL=debug` for debug logs. ## Agent Recipes Dexto comes with pre-built agent recipes for common use cases. Install and use them instantly: ```bash # List available agents dexto list-agents # Install specific agents dexto install nano-banana-agent podcast-agent coding-agent # Use an agent with one shot prompt dexto --agent nano-banana-agent --mode cli "create a futuristic cityscape with flying cars" dexto --agent podcast-agent --mode cli "generate a podcast intro with two hosts discussing AI" dexto --agent coding-agent --mode cli "create a landing page for a coffee brand inspired by star wars" # Alternatively, start the agent in web UI and put in the prompt yourself dexto --agent nano-banana-agent ``` **Available Agents:** - **Coding Agent** – Code generation, refactoring, debugging - **Nano Banana Agent** – Advanced image generation and editing using Google's Nano Banana (Gemini 2.5 Flash Image) - **Podcast Agent** – Advanced podcast generation using Google Gemini TTS for multi-speaker audio content - **Sora Video Agent** – AI video generation using OpenAI's Sora with custom settings, remixing, and reference support - **Database Agent** – Demo agent for SQL queries and database operations - **GitHub Agent** – GitHub operations, PR analysis, and repository management - **Image Editor Agent** – Image editing and manipulation - **Music Agent** – Music creation and audio processing - **Talk2PDF Agent** – Document analysis and conversation - **Product Researcher** – Product naming and branding research - **Triage Agent** – Demo multi-agent customer support routing system Each agent is pre-configured with the right tools, prompts, and LLM settings for its domain. No setup required—just install and start building. **📚 See the full [Agent Registry](https://docs.dexto.ai/docs/guides/agent-registry) for detailed information about all agents, their capabilities, use cases, and requirements.** More ready-to-run recipes live in [`agents/`](agents/). ## Examples & Demos ### 🎙️ Podcast Agent: Generate AI Podcasts **Task:** `Generate an intro for a podcast about the latest in AI.` ```bash dexto --agent podcast-agent ``` <img src="https://github.com/user-attachments/assets/cfd59751-3daa-4ccd-97b2-1b2862c96af1" alt="Podcast Agent Demo" width="600"/> ### 👁️ Computer Vision Agent: Face Detection & Annotation Using OpenCV **Task:** `Detect all faces in this image and draw bounding boxes around them.` ```bash dexto --agent image-editor-agent ``` <img src="https://github.com/user-attachments/assets/7e4b2043-c39a-47c7-a403-a9665ee762ce" alt="Face Detection Demo" width="600"> ### 🎮 Coding Agents: Create apps on demand Build full-stack applications, websites, and interactive games with AI-powered coding agents. Customize them to create your own coding agents. **Task:** `Can you create a snake game in a new folder and open it when done?` ```bash dexto --agent coding-agent ``` <img src=".github/assets/coding_agent_demo.gif" alt="Snake Game Development Demo" width="600"/> ### 📧 Portable Agents: Use your agents from Cursor Dexto agents are designed to be modular, composable and portable, allowing you to run them from anywhere. In this example, we connect to dexto as an MCP server via Cursor to use our podcast agent from above. <img src="https://github.com/user-attachments/assets/fd75a63f-4d29-447a-be24-6943e34c387f" alt="Email to Slack Demo" width="600"> ### 🎯 Triage Agent: Multi-Agent Customer Support Create multi-agent systems that can intelligently coordinate and delegate tasks among themselves based on the user query. ```bash dexto --agent triage-agent ``` <img src=".github/assets/triage_agent_demo.gif" alt="Triage Agent Demo" width="600"> ### 🛠️ Adding Custom MCP Servers You can add your own Model Context Protocol (MCP) servers to extend Dexto's capabilities with new tools or data sources. Just edit your agent YAML or add it directly in the WebUI. <img src="https://github.com/user-attachments/assets/1a3ca1fd-31a0-4e1d-ba93-23e1772b1e79" alt="Add MCP Server Example" width="600"/> ### 🧠 Memory: Persistent Context & Learning Create and save memories. Your agent automatically uses it to create personalized experiences. <img src=".github/assets/memory_demo.gif" alt="Memory Demo" width="600"> ### 🛒 MCP Store: Tool Discovery & Integration Equip your agents from 20+ MCP Servers and start using them via chat - instantly. - Bring your own keys - Can't find an MCP? [Contribute here!](https://github.com/truffle-ai/dexto/blob/main/CONTRIBUTING.md) <img src=".github/assets/mcp_store_demo.gif" alt="MCP Store Demo" width="600"> ### 📝 Human In The Loop: Dynamic Form Generation Agents can generate structured forms when they need additional data to make it easier to collect extra info & approvals from users. <img src=".github/assets/user_form_demo.gif" alt="User Form Demo" width="600"> #### More Examples: <details> <summary><strong>🛒 Browser Agent: Amazon Shopping Assistant</strong></summary> **Task:** `Can you go to amazon and add some snacks to my cart? I like trail mix, cheetos and maybe surprise me with something else?` ```bash # Default agent has browser tools dexto ``` <a href="https://youtu.be/C-Z0aVbl4Ik"> <img src="https://github.com/user-attachments/assets/3f5be5e2-7a55-4093-a071-8c52f1a83ba3" alt="Dexto: Amazon shopping agent demo" width="600"/> </a> </details> <details> <summary><strong>🎮 Playground: Interactive Development Environment</strong></summary> A testing playground to view the tools in your MCP servers before connecting them to LLMs to see the detailed response structures. <img src=".github/assets/playground_demo.gif" alt="Playground Demo" width="600"> </details> <details> <summary><strong>📧 Email to Slack: Automated Email Summaries</strong></summary> **Task:** `Summarize emails and send highlights to Slack` ```bash dexto --agent ./agents/examples/email_slack.yml ``` <img src="assets/email_slack_demo.gif" alt="Email to Slack Demo" width="600"> </details> <details> <summary><strong>🖼️ Hugging Face: Image Generation</strong></summary> **Task:** `Generate a photo of a baby panda.` <img src="https://github.com/user-attachments/assets/570cbd3a-6990-43c5-b355-2b549a4ee6b3" alt="Hugging Face Image Generation Demo" width="600"/> </details> --- ## Run Modes | Mode | Command | Best for | |------|---------|----------| | **Web UI** | `dexto` | Friendly chat interface w/ image support (default) | | **Interactive CLI** | `dexto --mode cli` | Everyday automation & quick tasks | | **Headless Server** | `dexto --mode server` | REST & WebSocket APIs for agent interaction | | **MCP Server (Agent)** | `dexto --mode mcp` | Exposing your agent as a tool for others via stdio | | **MCP Server (Aggregator)** | `dexto mcp --group-servers` | Re-exposing tools from multiple MCP servers via stdio | | **Discord Bot** | `dexto --mode discord` | Community servers & channels ([Requires Setup](packages/cli/src/discord/README.md)) | | **Telegram Bot** | `dexto --mode telegram` | Mobile chat ([Requires Setup](packages/cli/src/telegram/README.md)) | Run `dexto --help` for **all flags, sub-commands, and environment variables**. ## Configuration ### Agent Configuration Dexto treats each configuration as a unique agent allowing you to define and save combinations of LLMs, servers, storage options, etc. based on your needs for easy portability. Define agents in version-controlled YAML. Change the file, reload, and chat—state, memory, and tools update automatically. Example configuration: ```yaml # agents/my-agent.yml llm: provider: openai model: gpt-5-mini apiKey: $OPENAI_API_KEY mcpServers: filesystem: type: stdio command: npx args: ['-y', '@modelcontextprotocol/server-filesystem', '.'] web: type: stdio command: npx args: ['-y', '@modelcontextprotocol/server-brave-search'] systemPrompt: | You are a helpful AI assistant with access to files and web search. ``` ### LLM Providers Switch between providers instantly—no code changes required. | Provider | Models | Setup | |----------|--------|-------| | **OpenAI** | `gpt-5`, `gpt-5-mini`, `gpt-5-nano`, `gpt-4.1`, `gpt-4.1-mini`, `gpt-4.1-nano`, `gpt-4o`, `gpt-4o-mini`, `gpt-4o-audio-preview`, `o4-mini`, `o3`, `o3-mini`, `o1` | `change model in UI and add api key` | | **Anthropic** | `claude-haiku-4-5-20251001`, `claude-sonnet-4-5-20250929`, `claude-opus-4-1-20250805`, `claude-4-opus-20250514`, `claude-4-sonnet-20250514`, `claude-3-7-sonnet-20250219`, `claude-3-5-sonnet-20240620`, `claude-3-5-haiku-20241022` | `change model in UI and add api key` | | **Google** | `gemini-2.5-pro`, `gemini-2.5-flash`, `gemini-2.5-flash-lite`, `gemini-2.0-flash`, `gemini-2.0-flash-lite` | `change model in UI and add api key` | | **Groq** | `llama-3.3-70b-versatile`, `meta-llama/llama-4-scout-17b-16e-instruct`, `meta-llama/llama-4-maverick-17b-128e-instruct`, `qwen/qwen3-32b`, `gemma-2-9b-it`, `openai/gpt-oss-20b`, `openai/gpt-oss-120b`, `moonshotai/kimi-k2-instruct`, `deepseek-r1-distill-llama-70b` | `change model in UI and add api key` | | **xAI** | `grok-4`, `grok-3`, `grok-3-mini`, `grok-code-fast-1` | `change model in UI and add api key` | | **Cohere** | `command-a-03-2025`, `command-r-plus`, `command-r`, `command-r7b` | `change model in UI and add api key` | ```bash # Switch models via CLI dexto -m claude-sonnet-4-5-20250929 dexto -m gemini-2.5-pro ``` You can configure things like LLM, system prompt, MCP servers, storage, sessions, human-in-the loop, telemetry and more! See our [Configuration Guide](https://docs.dexto.ai/docs/category/agent-configuration-guide) for complete setup instructions. ## Programmatic API Install the `@dexto/core` library, and build applications with the `DextoAgent` class. Everything the CLI can do, your code can too. ```bash npm install @dexto/core ``` ```ts import { DextoAgent } from '@dexto/core'; // Create and start agent const agent = new DextoAgent({ llm: { provider: 'openai', model: 'gpt-5-mini', apiKey: process.env.OPENAI_API_KEY } }); await agent.start(); // Run tasks const response = await agent.run('List the 5 largest files in this repo'); console.log(response); // Hold conversations await agent.run('Write a haiku about TypeScript'); await agent.run('Make it funnier'); await agent.stop(); ``` See our [TypeScript SDK docs](https://docs.dexto.ai/api/category/dexto-sdk/) for complete examples with MCP tools, sessions, and advanced features. --- ## Advanced Usage ### Session Management Create and manage multiple conversation sessions with persistent storage. ```typescript const agent = new DextoAgent(config); await agent.start(); // Create and manage sessions const session = await agent.createSession('user-123'); await agent.run('Hello, how can you help me?', undefined, 'user-123'); // List and manage sessions const sessions = await agent.listSessions(); const sessionHistory = await agent.getSessionHistory('user-123'); await agent.deleteSession('user-123'); // Search across conversations const results = await agent.searchMessages('bug fix', { limit: 10 }); ``` ### LLM Management Switch between models and providers dynamically. ```typescript // Get current configuration const currentLLM = agent.getCurrentLLMConfig(); // Switch models (provider inferred automatically) await agent.switchLLM({ model: 'gpt-5-mini' }); await agent.switchLLM({ model: 'claude-sonnet-4-5-20250929' }); // Switch model for a specific session id 1234 await agent.switchLLM({ model: 'gpt-5-mini' }, '1234') // Get supported providers and models const providers = agent.getSupportedProviders(); const models = agent.getSupportedModels(); const openaiModels = agent.getSupportedModelsForProvider('openai'); ``` ### MCP Manager For advanced MCP server management, use the MCPManager directly. See the [MCP Manager SDK docs](https://docs.dexto.ai/api/sdk/mcp-manager) for full details. ```typescript import { MCPManager } from '@dexto/core'; const manager = new MCPManager(); // Connect to MCP servers await manager.connectServer('filesystem', { type: 'stdio', command: 'npx', args: ['-y', '@modelcontextprotocol/server-filesystem', '.'] }); // Access tools, prompts, and resources const tools = await manager.getAllTools(); const prompts = await manager.getAllPrompts(); const resources = await manager.getAllResources(); // Execute tools const result = await manager.executeTool('readFile', { path: './README.md' }); await manager.disconnectAll(); ``` ### Storage & Persistence Configure storage backends for production-ready persistence and caching. See the [Storage Configuration guide](https://docs.dexto.ai/docs/guides/configuring-dexto/storage) for full details. ```yaml # agents/production-agent.yml storage: cache: type: redis url: $REDIS_URL maxConnections: 100 database: type: postgres connectionString: $POSTGRES_CONNECTION_STRING maxConnections: 25 sessions: maxSessions: 1000 sessionTTL: 86400000 # 24 hours ``` **Supported Backends:** - **Cache**: Redis, In-Memory (fast, ephemeral) - **Database**: PostgreSQL, SQLite, In-Memory (persistent, reliable) **Use Cases:** - **Development**: In-memory for quick testing - **Production**: Redis + PostgreSQL for scale - **Simple**: SQLite for single-instance persistence See the [DextoAgent API Documentation](https://docs.dexto.ai/api/sdk/dexto-agent) for complete method references. --- ## CLI Reference <details> <summary>Click to expand for full CLI reference (`dexto --help`)</summary> ``` Usage: dexto [options] [command] [prompt...] Dexto CLI - AI-powered assistant with session management Basic Usage: dexto Start web UI (default) dexto "query" Run one-shot query (auto-uses CLI mode) dexto -p "query" Run one-shot query, then exit cat file | dexto -p "query" Process piped content CLI Mode: dexto --mode cli Start interactive CLI REPL Session Management: dexto -c Continue most recent conversation dexto -c -p "query" Continue with one-shot query, then exit dexto -r "<session-id>" "query" Resume with one-shot query Tool Confirmation: dexto --auto-approve Auto-approve all tool executions Agent Selection: dexto --agent coding-agent Use installed agent by name dexto --agent ./my-agent.yml Use agent from file path dexto -a agents/custom.yml Short form with relative path Advanced Modes: dexto --mode server Run as API server dexto --mode discord Run as Discord bot dexto --mode telegram Run as Telegram bot dexto --mode mcp Run as MCP server Session Commands: dexto session list|history|delete • search Search: dexto search <query> [--session <id>] [--role <role>] See https://docs.dexto.ai for documentation and examples Arguments: prompt Natural-language prompt to run once. If not passed, dexto will start as an interactive CLI Options: -v, --version output the current version -a, --agent <id|path> Agent ID or path to agent config file -p, --prompt <text> Run prompt and exit. Alternatively provide a single quoted string as positional argument. -s, --strict Require all server connections to succeed --no-verbose Disable verbose output --no-interactive Disable interactive prompts and API key setup --skip-setup Skip global setup validation (useful for MCP mode, automation) -m, --model <model> Specify the LLM model to use --router <router> Specify the LLM router to use (vercel or in-built) --auto-approve Always approve tool executions without confirmation prompts -c, --continue Continue most recent conversation -r, --resume <sessionId> Resume session by ID --mode <mode> The application in which dexto should talk to you - web | cli | server | discord | telegram | mcp (default: "web") --web-port <port> port for the web UI (default: 3000) (default: "3000") --api-port <port> port for the API server (default: web-port + 1) --no-auto-install Disable automatic installation of missing agents from registry -h, --help display help for command Commands: create-app Scaffold a new Dexto Typescript app init-app Initialize an existing Typescript app with Dexto setup [options] Configure global Dexto preferences install [options] [agents...] Install agents from registry or custom YAML files/directories uninstall [options] [agents...] Uninstall agents from the local installation list-agents [options] List available and installed agents which <agent> Show the path to an agent session Manage chat sessions search [options] <query> Search session history mcp [options] Start Dexto as an MCP server. Use --group-servers to aggregate and re-expose tools from configured MCP servers. In the future, this command will expose the agent as an MCP server by default. ``` </details> See the [CLI Guide](https://docs.dexto.ai/docs/guides/cli/overview) for full details. --- ## Next Steps * **[Quick Start](https://docs.dexto.ai/docs/getting-started/intro/)** – Get up and running in minutes. * **[Configuration Guide](https://docs.dexto.ai/docs/category/guides/)** – Configure agents, LLMs, and tools. * **[Building with Dexto](https://docs.dexto.ai/docs/category/tutorials/)** – Developer guides and patterns. * **[API Reference](https://docs.dexto.ai/api/)** – REST APIs, WebSocket, and SDKs. --- ## Telemetry We collect anonymous usage data (no personal/sensitive info) to help improve Dexto. This includes: - Commands used - Command execution time - Error occurrences - System information (OS, Node version) - LLM Models used To opt-out: Set env variable `DEXTO_ANALYTICS_DISABLED=1` ## Contributing We welcome contributions! Refer to our [Contributing Guide](./CONTRIBUTING.md) for more details. ## Community & Support Dexto is built by the team at [Truffle AI](https://www.trytruffle.ai). Join our Discord to share projects, ask questions, or just say hi! [](https://discord.gg/GFzWFAAZcm) If you enjoy Dexto, please give us a ⭐ on GitHub—it helps a lot! <div align="left"/> [](https://x.com/intent/user?screen_name=Road_Kill11) [](https://x.com/intent/user?screen_name=shaun5k_) </div> --- ## Contributors Thanks to all these amazing people for contributing to Dexto! [](https://github.com/truffle-ai/dexto/graphs/contributors) --- ## License Elastic License 2.0. See [LICENSE](LICENSE) for full terms. ", Assign "at most 3 tags" to the expected json: {"id":"15297","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"