| 1 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $10/mo |
| Capabilities | 9 decomposed | 13 decomposed |
| Times Matched | 0 | 0 |
Generates production-ready React/TypeScript UI components from natural language descriptions by routing requests through the CreateUiTool to the 21st.dev Magic API, which synthesizes component code and writes output files directly to the project filesystem. Uses a callback server (port 9221+) to handle asynchronous browser-based user interactions during generation, enabling iterative refinement without blocking the IDE.
Unique: Implements bidirectional IDE-to-API communication via MCP protocol with a dedicated callback server for handling asynchronous browser interactions, enabling real-time component generation with user feedback loops without leaving the IDE. Uses stdio transport for seamless IDE integration rather than HTTP polling.
vs alternatives: Faster than v0 for IDE workflows because it operates as a native MCP server in Cursor/Windsurf rather than requiring browser context switching, and directly writes files to the project instead of requiring manual copy-paste.
Refines existing React/TypeScript components through the RefineUiTool by sending current component code to the 21st.dev Magic API with refinement instructions, receiving improved code that addresses styling, accessibility, performance, or feature requests. Modifies existing component files in-place with API-generated improvements while maintaining component structure and imports.
Unique: Operates as an in-place component modifier through MCP rather than a separate linting or formatting tool, maintaining full component context and semantics while applying AI-driven improvements. Integrates directly with IDE file system for immediate feedback.
vs alternatives: More context-aware than ESLint or Prettier because it understands component intent and can refactor logic, not just formatting; faster than manual refactoring because it suggests improvements without requiring developer to articulate every change.
Retrieves pre-built React/TypeScript components from the 21st.dev component library through the FetchUiTool by querying the 21st.dev API with component names or descriptions, returning JSON-structured component data including code, props, and usage examples. Enables developers to discover and reuse existing components rather than generating new ones.
Unique: Provides MCP-native search and retrieval of a curated component library through structured API queries, returning rich metadata that includes not just code but props, examples, and design context. Operates as a discovery tool integrated into the IDE workflow.
vs alternatives: More discoverable than browsing npm registry because results are curated and pre-vetted by 21st.dev; faster than searching GitHub because queries are optimized for component metadata rather than full-text search.
Searches and retrieves company logos in multiple formats (SVG, JSX, TSX) through the LogoSearchTool by querying the SVGL API (api.svgl.app), enabling developers to quickly find and integrate brand logos into components. Returns logo data in multiple output formats suitable for different use cases (static SVG, React JSX components, TypeScript components).
Unique: Integrates SVGL API through MCP protocol with format conversion to JSX/TSX, allowing developers to search logos and receive them as ready-to-use React components without leaving the IDE. Provides multi-format output (SVG, JSX, TSX) from a single query.
vs alternatives: Faster than manually searching SVGL website and converting logos because it returns React-ready components directly; more integrated than copying SVGs because formats are optimized for different component use cases.
Implements MCP (Model Context Protocol) server communication using stdio transport, enabling the Magic MCP server to integrate seamlessly with IDE clients (Cursor, Windsurf, Cline) through stdin/stdout pipes. The McpServer instance handles request-response lifecycle, tool registration, and protocol compliance without requiring HTTP endpoints or external networking infrastructure.
Unique: Uses stdio-based MCP transport instead of HTTP, eliminating need for port management, external networking, or authentication infrastructure. McpServer instance manages full protocol lifecycle including signal handlers for graceful shutdown and error recovery.
vs alternatives: More reliable than HTTP-based tool servers because stdio is guaranteed by OS process model; lower latency than REST APIs because no serialization overhead; simpler deployment than microservices because no port conflicts or network configuration needed.
Manages asynchronous user interactions during component generation through a dedicated callback server (running on port 9221+) that handles browser-based UI flows without blocking the IDE. When CreateUiTool initiates generation requiring user input (e.g., design choices, refinements), the callback server receives responses and feeds them back to the generation pipeline, enabling interactive workflows.
Unique: Decouples IDE from browser-based user interactions through a dedicated callback server, allowing asynchronous workflows without blocking the IDE's MCP communication. Enables interactive component generation while maintaining IDE responsiveness.
vs alternatives: More responsive than blocking on user input because callback server handles async operations independently; better UX than modal dialogs because users can interact with browser UI while IDE remains responsive; more flexible than synchronous APIs because supports multi-step workflows.
Provides a unified HTTP client (twentyFirstClient) that abstracts communication with multiple external APIs (21st.dev Magic API and SVGL API) through a single interface. Handles request serialization, response parsing, error handling, and retry logic, enabling tools to invoke external services without managing HTTP details directly.
Unique: Centralizes HTTP communication for multiple external APIs (21st.dev Magic, SVGL) through a single client interface, abstracting API-specific details and enabling consistent error handling and retry logic across all tools.
vs alternatives: More maintainable than scattered HTTP calls because API changes require updates in one place; more reliable than direct fetch calls because includes built-in error handling and retry logic; easier to test because HTTP layer is mocked at client level.
Registers four specialized tools (CreateUiTool, RefineUiTool, FetchUiTool, LogoSearchTool) with the MCP server, enabling the IDE to discover available capabilities and route tool invocations to appropriate handlers. Each tool extends the MCP tool interface with specific input schemas, descriptions, and execution logic, allowing the IDE to validate inputs before execution.
Unique: Implements tool registration as MCP protocol-compliant handlers with input schema validation, enabling IDE-side input validation and tool discovery without requiring separate documentation or configuration files.
vs alternatives: More discoverable than function calling APIs because tools are registered with full metadata; more type-safe than string-based routing because input schemas are validated before execution; more maintainable than hardcoded tool lists because registration is declarative.
+1 more capabilities
Generates single-line and multi-line code suggestions in real-time as developers type, using semantic indexing of the entire codebase to retrieve relevant type definitions, function signatures, and contextual patterns. The system maintains a 1M token context window (Pro/Team tiers) that enables suggestions informed by distant code definitions and cross-file dependencies, constructed via local codebase semantic search rather than simple token-based recency. Suggestions adapt to detected coding style on Pro/Team tiers through implicit pattern learning from recent edits.
Unique: 1M token context window with codebase-wide semantic indexing enables suggestions informed by distant code definitions and cross-file patterns, versus competitors (Copilot, Tabnine) that typically use fixed context windows (4K-32K tokens) or file-local context. Claimed 250ms latency suggests optimized retrieval pipeline, though indexing mechanism and performance at scale remain undisclosed.
vs alternatives: Larger context window than GitHub Copilot (8K-32K tokens) and faster latency than unnamed competitors (250ms vs 783ms claimed), enabling suggestions on large codebases with minimal typing delay; trade-off is cloud dependency and undisclosed free tier limitations.
Provides a separate chat interface supporting multiple LLM backends (GPT-4o, Claude 3.5 Sonnet, GPT-4, others) for conversational code assistance. Users attach files, reference recent edits, and trigger compiler diagnostic uploads; the system generates diffs and applies code changes directly to the editor. Model selection is per-conversation, and $5/month in credits (included in Pro/Team) covers external model API costs; overage pricing is undisclosed. Hotkey-driven workflow enables rapid context switching between inline completion and chat.
Unique: Multi-model chat interface with per-conversation model selection and integrated diff application, combined with compiler diagnostic auto-upload. Unlike Copilot Chat (single model per tier) or standalone ChatGPT, Supermaven Chat unifies multiple LLM backends in a single hotkey-driven workflow with direct editor integration for change application.
Supermaven scores higher at 71/100 vs magic-mcp at 33/100. magic-mcp leads on ecosystem, while Supermaven is stronger on adoption and quality.
Need something different?
Search the match graph →© 2026 Unfragile. Stronger through disorder.
vs alternatives: Supports multiple LLM backends (GPT-4o, Claude 3.5 Sonnet) in one interface with included credits, whereas GitHub Copilot Chat is single-model per tier and requires separate ChatGPT subscription for model switching; trade-off is credit limits and unknown overage pricing.
Supermaven Chat can automatically upload compiler diagnostic messages (errors, warnings) alongside code context to provide error-aware suggestions and fixes. The mechanism is described as 'automatically uploading your code together with compiler diagnostic messages,' but specific language/compiler support and the upload trigger mechanism are undisclosed. This feature is Chat-only and not available in inline completion.
Unique: Automatic compiler diagnostic upload in Chat for error-aware suggestions, versus competitors (Copilot, Tabnine) that require manual error context or have limited diagnostic integration. Supermaven's approach reduces friction but with undisclosed language/compiler support.
vs alternatives: Automatic diagnostic upload reduces manual context-gathering compared to manual copy-paste; trade-off is undisclosed language support and unclear upload trigger mechanism.
Supermaven offers a 30-day free trial of the Pro tier ($10/month), providing full access to 1M token context window, largest model, style adaptation, and $5/month chat credits. No credit card is required to start the trial (implied), and trial conversion to paid is automatic after 30 days unless cancelled. Trial terms and auto-renewal policy are not explicitly detailed.
Unique: 30-day free trial of Pro tier with full feature access (1M context, largest model, chat credits), versus competitors (Copilot 2-month free trial, Tabnine free tier only) with different trial lengths and feature access. Supermaven's approach is generous but with undisclosed auto-renewal terms.
vs alternatives: Full Pro feature access during trial compared to limited free tier; trade-off is undisclosed auto-renewal policy and potential unexpected charges if not cancelled.
Supermaven requires internet connectivity and server-side inference; no offline mode or local inference capability is mentioned or available. All code completion requests are sent to Supermaven's backend servers for processing, and responses are returned over the network. This creates a hard dependency on network connectivity and Supermaven's service availability; if the service is down or network is unavailable, code completion is not available.
Unique: Supermaven has no offline mode or local inference capability; all processing is server-side. GitHub Copilot also requires server-side inference, but Tabnine offers local inference options for some use cases. Supermaven's lack of offline capability is a significant limitation for developers with connectivity constraints.
vs alternatives: Supermaven's server-side-only approach is comparable to GitHub Copilot; Tabnine offers local inference options, making Tabnine more suitable for offline work. Supermaven's lack of offline capability is a weakness vs. Tabnine.
Analyzes recent code edits and inferred coding patterns to adapt inline suggestions to match team conventions, naming patterns, and structural preferences. The mechanism is implicit (not explicit fine-tuning) and operates only on Pro/Team tiers, suggesting pattern learning from editor activity rather than explicit configuration. Free tier uses a single base model without personalization.
Unique: Implicit style adaptation via editor activity analysis without explicit configuration, versus competitors (Copilot, Tabnine) that require manual style guides or explicit fine-tuning. Supermaven's approach is transparent to the user but also non-configurable and undisclosed in mechanism.
vs alternatives: Requires no manual style configuration compared to tools requiring explicit style guides; trade-off is lack of transparency and inability to control or export learned styles.
Delivers code suggestions to the editor inline as the developer types, with a claimed baseline latency of 250ms from keystroke to suggestion display. The system uses a cloud inference backend and local editor plugin to minimize round-trip time. Latency claim is positioned against an unnamed competitor (783ms), but methodology is undisclosed and no independent verification is provided.
Unique: Claimed 250ms latency via optimized cloud inference pipeline and editor plugin architecture, versus competitors with higher latency (783ms unnamed baseline). Actual differentiation is undisclosed; mechanism may involve request batching, model quantization, or edge caching, but specifics are not public.
vs alternatives: Faster than unnamed competitor (250ms vs 783ms claimed); trade-off is cloud dependency and unverified latency claim with no SLA or performance guarantee.
Provides native editor extensions for VS Code, JetBrains IDEs (IntelliJ IDEA, PyCharm, WebStorm, etc.), and Neovim, enabling inline suggestion rendering, hotkey-driven chat access, and compiler diagnostic integration directly within the editor. Each plugin variant is maintained separately and integrates with the editor's native autocomplete UI, keybinding system, and file context APIs.
Unique: Native plugins for three major editor ecosystems (VS Code, JetBrains, Neovim) with integrated chat and diff application, versus competitors (Copilot, Tabnine) that support broader editor ecosystems but with less deep integration in some cases. Supermaven's approach prioritizes depth over breadth.
vs alternatives: Deep integration with VS Code and JetBrains (native autocomplete UI, hotkey system) compared to web-based tools or lighter integrations; trade-off is limited editor support (no Sublime, Vim, Emacs) and undisclosed Neovim support details.
+5 more capabilities