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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
An on-device developer memory tool that auto-captures code, docs and context across apps so engineers can search and reuse it later.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Unified API gateway to 500+ AI models (GPT, Claude, Sora, image/video) with OpenAI-compatible endpoints and discounted usage.
No public pricing
No public pricing
No public pricing
No public pricing
No public pricing
- ✦CSV to API conversion
- ✦Data parsing (CSV to JSON)
- ✦Filtering capabilities
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Automatic capture of code, docs and context across apps
- ✦Long-term memory engine for time-based search of past work
- ✦One-click save, search and AI-tagging of code snippets
- ✦Local, on-device processing with optional cloud sync
- ✦Plugin support for browsers and IDEs like VS Code
- ✦MCP integration with external LLMs for contextual answers
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Single OpenAI-compatible API for 500+ models
- ✦Chat, image, video and audio models
- ✦Discounted per-request pricing
- ✦One dashboard for keys, quotas and usage
- ✦Multi-region routing and failover (99.9% uptime)
- ✦Multiple payment methods incl. crypto
- →Sharing CSV data with a team via an API
- →Creating a public API from CSV data
- →Filtering and accessing specific data within a CSV file programmatically
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Recalling code snippets and context from past coding sessions
- →Feeding accurate personal context into AI coding assistants
- →Keeping research notes and links without manual bookmarking
- →Preserving shared context across team collaboration tools
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Accessing many AI models via one API
- →Cutting AI model API costs
- →Building multimodal AI apps
- →Consolidating AI billing and keys
