Scira

Research at the speed of thought. The agentic research platform that plans, retrieves, and cites — so you can think faster.

🔗 Try Scira at scira.ai

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Special Thanks

How It Works

1. Ask anything — Type a question, upload a PDF, or paste a URL. Pick a mode or let Scira decide for you.
2. Scira plans & retrieves — The agent breaks your question into sub-tasks, searches live sources, and cross-checks the evidence.
3. Get cited answers — Receive a grounded answer with inline citations. Click any source to verify it yourself.

Features

Core Capabilities

• Agentic Planning — Breaks complex questions into steps, selects the right models and tools, then executes multi-step workflows end to end
• Grounded Retrieval — Every answer comes with inline citations you can click to audit the evidence yourself
• Extensible & Open — AGPL-3.0 licensed. Self-host, bring your own models, connect custom tools, and tailor everything to your workflow
• Lookouts — Schedule recurring research agents that monitor topics, track changes, and email you updates

Search Modes (17 modes)

Mode	Description
Web	Search the entire web with AI-powered analysis
Chat	Talk to the model directly, no search
X	Real-time posts, trends, and conversations
Stocks	Market data, charts, and financial analysis
Code	Get context about languages and frameworks
Academic	Research papers, citations, and scholarly sources
Extreme	Deep research with multiple sources and analysis
Reddit	Discussions, opinions, and community insights
GitHub	Repositories, code, and developer discussions
Crypto	Cryptocurrency research powered by CoinGecko
Prediction	Prediction markets from Polymarket and Kalshi
YouTube	Video summaries, transcripts, and analysis
Spotify	Search songs, artists, and albums
Connectors	Search Google Drive, Notion & OneDrive (Pro)
Memory	Your personal memory companion (Pro)
Voice	Conversational AI with real-time voice (Pro)
XQL	Advanced X query language for tweet analysis (Pro)

Tools (28 tools)

Search & Retrieval

• Web search — Multi-query parallel web search with deduplication using Exa, Firecrawl, Parallel, and Tavily
• Extreme search — LLM-driven deep research agent with multi-step planning, code execution, and R2 artifact storage
• Academic search — Search academic papers and research using Exa and Firecrawl
• Reddit search — Search Reddit with configurable time ranges using Parallel
• X search — Search X posts with date range filtering and handle inclusion/exclusion using xAI Grok
• YouTube search — Search videos, channels, playlists with transcript extraction using Supadata
• GitHub search — Search repositories with structured metadata extraction using Firecrawl
• Spotify search — Search tracks, artists, albums, and playlists via Spotify Web API
• URL content retrieval — Extract content from any URL including tweets, YouTube, TikTok, and Instagram

Financial & Market Data

• Stock charts — Interactive stock charts with OHLC data, earnings, and news using Valyu, Tavily, and Exa
• Currency converter — Forex and crypto conversion with real-time rates using Valyu
• Crypto tools — Cryptocurrency data, contract lookups, and OHLC charts using CoinGecko
• Prediction markets — Query Polymarket and Kalshi data with Cohere reranking using Valyu

Location & Travel

• Weather — Current weather, 5-day forecast, air quality, and 16-day extended forecast using OpenWeatherMap and Open-Meteo
• Maps & geocoding — Forward/reverse geocoding and nearby place discovery using Google Maps API
• Flight tracking — Real-time flight status with departure/arrival details

Media & Entertainment

• Movie/TV search — Search movies and TV shows with detailed cast, ratings, and metadata using TMDB
• Trending movies — Today’s trending movies from TMDB
• Trending TV shows — Today’s trending TV shows from TMDB

Productivity & Utilities

• Code interpreter — Write and execute Python code in a sandboxed Daytona environment with chart generation
• Code context — Get contextual information about programming topics using Exa Context API
• Text translation — Translate text (and text within images) between languages using AI models
• File query search — Semantic search over uploaded files (PDF, CSV, DOCX, Excel) with Cohere embeddings and reranking
• Connectors search — Search connected Google Drive, Notion, and OneDrive using Supermemory
• Memory tools — Save and search personal memories using Supermemory
• Date & time — Current date/time in multiple formats with timezone support
• Greeting — Personalized time-of-day-aware greetings

LLM Models Supported

• xAI: Grok 3, Grok 3 Mini, Grok 4, Grok 4 Fast, Grok 4.1 Fast, Grok Code
• OpenAI: GPT 4.1 (Nano/Mini/Standard), GPT 5 (Nano/Mini/Medium/Standard), GPT 5.1 (Instant/Thinking/Codex), GPT 5.2 (Instant/Thinking/Codex), o3, o4 mini, GPT OSS 20B/120B
• Anthropic: Claude Haiku 4.5, Claude Sonnet 4.5, Claude 4.5 Opus, Claude 4.6 Opus
• Google: Gemini 2.5 Flash (Lite/Standard), Gemini 2.5 Pro, Gemini 3 Flash, Gemini 3 Pro
• Alibaba (Qwen): Qwen 3 (4B/32B/235B), Qwen 3 VL, Qwen 3 Max, Qwen 3 Coder (Small/Standard/Plus/Next), Qwen 3 Next 80B
• Mistral: Ministral 3 (3B/8B/14B), Mistral Large 3, Mistral Medium, Magistral (Small/Medium), Devstral 2 (Small/Standard)
• DeepSeek: DeepSeek v3, v3.1 Terminus, v3.2, R1, R1 0528
• Zhipu (GLM): GLM 4.5, GLM 4.5 Air, GLM 4.6, GLM 4.6V, GLM 4.7, GLM 4.7 Flash
• Cohere: Command A, Command A Thinking
• MoonShot: Kimi K2, Kimi K2.5
• Minimax: M1 80K, M2, M2.1, M2.1 Lightning
• ByteDance: Seed 1.6, Seed 1.6 Flash, Seed 1.8
• Arcee: Trinity Mini, Trinity Large
• Others: Vercel v0 (1.0/1.5), Amazon Nova 2 Lite, Xiaomi Mimo V2 Flash, StepFun Step 3.5 Flash, Kwaipilot KAT-Coder-Pro V1

Built with

• Next.js - React framework
• Tailwind CSS - Styling
• Vercel AI SDK - AI model integration and streaming
• Shadcn/UI - UI components
• Exa.AI - Web search, academic search, and content retrieval
• Firecrawl - Web scraping with structured extraction
• Parallel - Web and Reddit search
• Tavily - Web search and financial news
• Valyu - Financial data, forex, and prediction markets
• Supadata - YouTube search, transcripts, and social media
• CoinGecko - Cryptocurrency market data
• Spotify - Music search
• OpenWeatherMap - Weather data
• Open-Meteo - Extended forecasts and geocoding
• Daytona - Code execution sandbox
• Google Maps - Geocoding and places
• TMDB - Movie and TV data
• Cohere - Embeddings and reranking
• Supermemory - Memory management and connector search
• Upstash - Serverless Redis and rate limiting
• Cloudflare R2 - Object storage for artifacts
• ElevenLabs - Voice synthesis
• Better Auth - Authentication
• Drizzle ORM - Database management
• Novita AI - AI Inference

Deploy your own

Set Scira as your default search engine

1. Open the Chrome browser settings:

   • Click on the three vertical dots in the upper right corner of the browser.
   • Select “Settings” from the dropdown menu.

2. Go to the search engine settings:

   • In the left sidebar, click on “Search engine.”
   • Then select “Manage search engines and site search.”

3. Add a new search engine:

   • Click on “Add” next to “Site search.”

4. Set the search engine name:

   • Enter Scira in the “Search engine” field.

5. Set the search engine URL:

   • Enter https://scira.ai?q=%s in the “URL with %s in place of query” field.

6. Set the search engine shortcut:

   • Enter sh in the “Shortcut” field.

7. Set Default:

   • Click on the three dots next to the search engine you just added.
   • Select “Make default” from the dropdown menu.

After completing these steps, you should be able to use Scira as your default search engine in Chrome.

Local development

Run via Docker

The application can be run using Docker in two ways:

Using Docker Compose (Recommended)

1. Make sure you have Docker and Docker Compose installed on your system
2. Create a .env file based on .env.example with your API keys
3. Run the following command in the project root:

   docker compose up

4. The application will be available at http://localhost:3000

Using Docker Directly

1. Create a .env file based on .env.example with your API keys
2. Build the Docker image:

   docker build -t scira.app .

3. Run the container:

   docker run --env-file .env -p 3000:3000 scira.app

The application uses a multi-stage build process to minimize the final image size and implements security best practices. The production image runs on Node.js LTS with Alpine Linux for a minimal footprint.

Run with Node.js

To run the application locally without Docker:

1. Sign up for accounts with the required AI providers:
   • OpenAI (required)
   • Anthropic (required)
   • Exa (required for web search feature)
2. Copy .env.example to .env.local and fill in your API keys
3. Install dependencies:

   pnpm install

4. Start the development server:

   pnpm dev

5. Open http://localhost:3000 in your browser

License

This project is licensed under the AGPLv3 License - see the LICENSE file for details.