{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-cherryhq--cherry-studio","slug":"cherryhq--cherry-studio","name":"cherry-studio","type":"agent","url":"https://cherry-ai.com","page_url":"https://unfragile.ai/cherryhq--cherry-studio","categories":["ai-agents"],"tags":["agency-agents","ai-agent","claude-code","codex","open-cli","openclaw","opencode","skills","superpowers","vibe-coding"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-cherryhq--cherry-studio__cap_0","uri":"capability://tool.use.integration.multi.provider.llm.unified.interface.with.provider.abstraction.layer","name":"multi-provider llm unified interface with provider abstraction layer","description":"Cherry Studio abstracts 50+ LLM providers (OpenAI, Anthropic, DeepSeek, Ollama, etc.) through a unified API service layer that handles provider-specific parameter construction, API key rotation, and streaming response normalization. The Provider System maps model configurations to provider-specific implementations, enabling seamless switching between providers without changing application logic. This is implemented via a service-oriented architecture where each provider has a dedicated adapter that translates Cherry Studio's canonical request format into provider-specific API calls.","intents":["Switch between different LLM providers without reconfiguring the entire application","Use multiple provider API keys simultaneously with automatic rotation","Access frontier models from different vendors in a single unified chat interface","Configure provider-specific parameters (temperature, top_p, reasoning effort) per model"],"best_for":["Teams evaluating multiple LLM providers without vendor lock-in","Developers building multi-model AI applications requiring provider flexibility","Organizations with existing relationships with multiple LLM vendors"],"limitations":["Provider-specific parameter differences may not be fully normalized — some advanced parameters only work with specific providers","Streaming response latency varies by provider; no built-in response time optimization across providers","API key management is local-only — no centralized key rotation service for enterprise deployments"],"requires":["API keys for at least one LLM provider (OpenAI, Anthropic, DeepSeek, etc.)","Network connectivity to provider endpoints","TypeScript/Node.js runtime for local API server"],"input_types":["text prompts","model configuration objects","API credentials"],"output_types":["streamed text responses","structured JSON completions","token usage metadata"],"categories":["tool-use-integration","multi-provider-abstraction"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_1","uri":"capability://planning.reasoning.autonomous.agent.orchestration.with.tool.execution.and.mcp.integration","name":"autonomous agent orchestration with tool execution and mcp integration","description":"Cherry Studio implements an Agent System that orchestrates multi-step reasoning workflows by decomposing user intents into subtasks, executing tools via the Model Context Protocol (MCP), and managing agent state across iterations. Agents can invoke MCP tools (code execution, file operations, web search) through a standardized tool registry, with responses fed back into the reasoning loop. The MCP Architecture manages server lifecycle, tool discovery, and execution sandboxing, while the Agent System maintains conversation context and decision history across multiple reasoning steps.","intents":["Create autonomous agents that can plan, execute code, and iterate toward solving complex problems","Chain multiple tool calls together with intermediate reasoning steps","Execute code in isolated environments without exposing the host system","Build agents that can search the web, read files, and modify code autonomously"],"best_for":["Developers building autonomous coding assistants or research agents","Teams automating multi-step workflows that require reasoning between tool calls","Users who need agents to execute code safely without direct system access"],"limitations":["Agent reasoning latency compounds with each tool call — no built-in optimization for reducing reasoning steps","Tool execution is sequential; no parallel tool invocation support","MCP server lifecycle management is local-only — no distributed agent execution across machines","Agent state is stored in Redux; no built-in persistence layer for long-running agents across application restarts"],"requires":["MCP servers configured and running (local or remote)","LLM provider with function-calling support (OpenAI, Anthropic, etc.)","Node.js 18+ for local tool execution","Proper file system permissions for code execution tools"],"input_types":["natural language task descriptions","tool schemas (JSON)","MCP server configurations"],"output_types":["agent execution traces","tool call results","final reasoning conclusions"],"categories":["planning-reasoning","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_10","uri":"capability://tool.use.integration.local.api.server.with.oauth.integration.and.lan.file.transfer","name":"local api server with oauth integration and lan file transfer","description":"Cherry Studio exposes a local API server that enables external applications to interact with the application via HTTP. The Local API Server provides REST endpoints for chat, assistant management, and knowledge base operations. OAuth Integration enables secure authentication for API access, supporting both local and cloud-based OAuth providers. LAN Transfer and File Management enables users to transfer files between devices on the same network without cloud storage, using local network discovery and peer-to-peer transfer.","intents":["Integrate Cherry Studio with external applications via REST API","Enable secure API access through OAuth authentication","Transfer files between devices on the same network without cloud storage","Build mobile or web clients that communicate with Cherry Studio backend"],"best_for":["Teams building integrations with Cherry Studio from external tools","Organizations requiring local-only file transfer for privacy","Developers building mobile/web clients for Cherry Studio"],"limitations":["Local API server is not production-grade — no rate limiting or DDoS protection","OAuth integration is basic — no support for advanced flows (PKCE, device flow)","LAN transfer is limited to local network — no support for remote transfer","API documentation is minimal — requires reverse-engineering from source code"],"requires":["Local API server enabled in settings","Network access to local machine (localhost or LAN)","OAuth provider configuration (optional)"],"input_types":["HTTP requests","OAuth credentials","file data"],"output_types":["HTTP responses","OAuth tokens","transferred files"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_11","uri":"capability://text.generation.language.rich.text.editor.and.notes.system.with.markdown.support.and.formatting","name":"rich text editor and notes system with markdown support and formatting","description":"Cherry Studio includes a Notes and Rich Text Editor that enables users to create and edit rich text documents with markdown support. The editor supports inline formatting (bold, italic, code), lists, tables, and code blocks with syntax highlighting. Notes are persisted to the local database and can be linked to conversations or assistants. The system provides a WYSIWYG editing experience with markdown preview, enabling users to write documentation or notes alongside AI conversations.","intents":["Create and organize notes alongside AI conversations","Write markdown documents with rich formatting and syntax highlighting","Link notes to conversations or assistants for context management","Export notes in markdown or HTML format"],"best_for":["Researchers documenting findings alongside AI analysis","Teams creating knowledge bases from AI conversations","Individual users building personal knowledge management systems"],"limitations":["Rich text editor is basic — no support for advanced formatting (tables, embedded media)","Notes are single-user only — no collaborative editing","No version control or change tracking — overwrites are permanent","Markdown preview is client-side only — no server-side rendering"],"requires":["Local database for note persistence","React component library for editor UI"],"input_types":["markdown text","formatted content"],"output_types":["persisted notes","exported markdown/HTML","linked context"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_12","uri":"capability://text.generation.language.theme.and.localization.system.with.multi.language.support.and.dark.mode","name":"theme and localization system with multi-language support and dark mode","description":"Cherry Studio implements a Theme and Localization system that supports multiple languages (English, Chinese, etc.) and theme modes (light, dark, auto). The system uses a localization framework to manage translated strings, with language selection persisted in settings. Theme switching is implemented via CSS variables and React context, enabling instant theme changes without page reload. The system respects system theme preferences and enables manual override.","intents":["Use Cherry Studio in preferred language with full UI localization","Switch between light and dark themes based on preference or time of day","Contribute translations for new languages","Customize theme colors and appearance"],"best_for":["International teams requiring multi-language support","Users with accessibility needs (dark mode, high contrast)","Open-source contributors adding language support"],"limitations":["Language switching requires application restart — no hot-reload of translations","Theme customization is limited to predefined themes — no custom color picker","Right-to-left (RTL) language support is incomplete — layout may not adapt properly","Localization strings are hardcoded — no dynamic translation loading"],"requires":["Language selection in settings","Browser/OS theme preference support"],"input_types":["language code","theme preference"],"output_types":["localized UI strings","themed CSS","persisted preferences"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_13","uri":"capability://automation.workflow.auto.update.system.with.background.updates.and.version.management","name":"auto-update system with background updates and version management","description":"Cherry Studio implements an Auto-Update System that checks for new versions in the background, downloads updates, and prompts users to install. The system uses electron-updater for update management, with support for staged rollouts and update channels (stable, beta). Updates are downloaded in the background without blocking the application, and users can defer installation until a convenient time. The system maintains version history and enables rollback to previous versions.","intents":["Keep Cherry Studio up-to-date with latest features and security patches","Receive notifications about available updates without disrupting workflow","Test beta features before stable release","Rollback to previous version if update causes issues"],"best_for":["Individual users wanting automatic security updates","Teams managing Cherry Studio deployments across multiple machines","Beta testers wanting early access to new features"],"limitations":["Update checks are periodic — may not detect updates immediately","Rollback is manual — no automatic rollback on update failure","Update channels are global — no per-user channel selection","Staged rollouts are not configurable — all users get updates simultaneously"],"requires":["Network connectivity to update server","Sufficient disk space for update download"],"input_types":["version information","update channel preference"],"output_types":["update notifications","downloaded updates","version history"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_14","uri":"capability://text.generation.language.selection.assistant.and.context.menu.integration.for.system.wide.ai.access","name":"selection assistant and context menu integration for system-wide ai access","description":"Cherry Studio implements a Selection Assistant that integrates with the system context menu, enabling users to select text anywhere on the system and send it to Cherry Studio for analysis or processing. The system uses Electron's native context menu APIs to register custom menu items. When text is selected, users can choose from predefined actions (translate, summarize, explain, etc.) which are executed by the appropriate assistant. Results can be displayed in a floating window or copied to clipboard.","intents":["Quickly analyze or process selected text without switching to Cherry Studio","Translate selected text using AI without leaving current application","Get explanations or summaries of selected content","Build system-wide AI workflows that integrate with native applications"],"best_for":["Power users working with multiple applications simultaneously","Teams using AI for content analysis across various tools","Users wanting quick AI access without context switching"],"limitations":["Context menu integration is OS-specific — implementation differs for Windows/Mac/Linux","Selection assistant actions are predefined — no dynamic action discovery","Results are displayed in floating window — no integration with source application","System-wide access requires elevated permissions — may trigger security warnings"],"requires":["Electron context menu API support","OS-specific implementation for each platform","Appropriate system permissions"],"input_types":["selected text","action selection"],"output_types":["processed text","floating window results","clipboard content"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_15","uri":"capability://image.visual.image.generation.and.painting.tools.with.model.integration","name":"image generation and painting tools with model integration","description":"Cherry Studio integrates image generation capabilities through connected LLM providers that support image generation (DALL-E, Midjourney, etc.). The Paintings and Image Generation system enables users to generate images from text prompts within the chat interface. Generated images are displayed inline in conversations and can be saved or edited. The system supports image-to-image editing and variation generation. Integration with MCP tools enables advanced image processing (upscaling, background removal, etc.).","intents":["Generate images from text descriptions within chat conversations","Create variations of generated images with different prompts","Edit images using AI-powered tools (background removal, upscaling)","Build creative workflows combining text and image generation"],"best_for":["Content creators generating visual assets","Designers prototyping ideas with AI","Teams building creative workflows with AI"],"limitations":["Image generation is provider-dependent — quality and speed vary by provider","Image editing tools are limited to available MCP tools — no built-in editing","Generated images are not automatically saved — requires manual export","No batch image generation — one image at a time"],"requires":["LLM provider with image generation support (DALL-E, Midjourney, etc.)","API key for image generation service","MCP tools for advanced image processing (optional)"],"input_types":["text prompts","image files","editing parameters"],"output_types":["generated images","edited images","image metadata"],"categories":["image-visual","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_2","uri":"capability://memory.knowledge.knowledge.base.system.with.rag.enabled.semantic.search.and.document.ingestion","name":"knowledge base system with rag-enabled semantic search and document ingestion","description":"Cherry Studio implements a Knowledge Base System that ingests documents (PDFs, markdown, text) through a document processing pipeline with OCR support, generates embeddings for semantic search, and retrieves relevant context for RAG-augmented chat. The system stores documents in a local database with metadata indexing, enabling full-text and semantic search across ingested knowledge. When a user queries, the system retrieves relevant document chunks and injects them into the LLM context, enabling the model to answer questions grounded in custom knowledge.","intents":["Upload and index custom documents to augment LLM responses with proprietary knowledge","Search across ingested documents using semantic similarity rather than keyword matching","Extract text from PDFs and images using OCR for knowledge base ingestion","Ground LLM responses in specific documents with citation tracking"],"best_for":["Teams building domain-specific AI assistants with proprietary documentation","Researchers managing large document collections with semantic search needs","Organizations needing to keep knowledge bases local for privacy/compliance"],"limitations":["Embedding generation is local-only — no support for cloud embedding services, limiting scalability to large document collections","OCR accuracy depends on document quality; no built-in OCR confidence scoring or manual correction workflow","Semantic search requires pre-computed embeddings; no dynamic re-indexing on document updates","No built-in deduplication or chunk overlap management — may retrieve redundant context"],"requires":["Local embedding model or API key for embedding service","Sufficient disk space for document storage and embeddings","PDF/image processing libraries (included in Electron distribution)","LLM provider with context window large enough for RAG injection"],"input_types":["PDF files","markdown documents","plain text files","images with text (OCR)"],"output_types":["document chunks with metadata","embedding vectors","search results with relevance scores","augmented LLM responses with citations"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_3","uri":"capability://text.generation.language.customizable.assistant.system.with.role.based.prompting.and.skill.composition","name":"customizable assistant system with role-based prompting and skill composition","description":"Cherry Studio provides an Assistant System that enables creation of custom AI assistants with predefined roles, system prompts, and skill compositions. Assistants are defined as configuration objects specifying model, provider, system prompt, and enabled skills. The system includes 300+ pre-built assistants covering various domains (coding, writing, analysis, etc.). When a user selects an assistant, Cherry Studio injects the assistant's system prompt and skills into the conversation context, enabling role-specific behavior without requiring manual prompt engineering.","intents":["Create domain-specific AI assistants (code reviewer, technical writer, data analyst) with predefined expertise","Share custom assistant configurations with team members","Compose assistants from reusable skills (web search, code execution, document analysis)","Switch between different assistant personalities within the same chat session"],"best_for":["Teams standardizing AI assistant configurations across projects","Individual developers building specialized assistants for repetitive tasks","Organizations creating branded AI assistants for customer-facing applications"],"limitations":["Assistant configurations are stored locally — no built-in sharing mechanism for team collaboration","Skills are predefined; no dynamic skill composition at runtime","System prompts are static — no context-aware prompt adaptation based on conversation history","No versioning or rollback mechanism for assistant configuration changes"],"requires":["LLM provider API key","Model selection from configured providers","Optional: MCP servers for skill execution"],"input_types":["assistant configuration JSON","system prompt text","skill definitions"],"output_types":["assistant metadata","configured chat sessions","skill execution results"],"categories":["text-generation-language","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_4","uri":"capability://memory.knowledge.multi.session.chat.management.with.topic.organization.and.conversation.persistence","name":"multi-session chat management with topic organization and conversation persistence","description":"Cherry Studio implements a Topic and Session Management system that organizes conversations into topics (folders), with each topic containing multiple chat sessions. Conversations are persisted to a local database with full message history, metadata (timestamps, model used, tokens), and session state. The Message System handles message rendering, streaming responses, and markdown/code block formatting. Redux state management maintains the current session context, enabling seamless switching between conversations while preserving full history and context.","intents":["Organize multiple conversations into topics for better knowledge management","Resume previous conversations with full context and history","Search across all conversations to find previous answers or discussions","Export conversations in multiple formats (markdown, JSON, PDF)"],"best_for":["Researchers managing multiple research threads across conversations","Teams collaborating on projects with shared conversation history","Individual users building personal knowledge bases from AI conversations"],"limitations":["Conversation search is local-only — no full-text indexing across large conversation collections","No built-in conversation sharing mechanism — requires manual export/import","Message persistence is single-user — no multi-user collaboration on shared conversations","Topic hierarchy is flat — no nested topic organization"],"requires":["Local database (SQLite or equivalent) for message persistence","Sufficient disk space for conversation history","Redux state management for session context"],"input_types":["user messages","LLM responses","metadata (model, provider, tokens)"],"output_types":["persisted conversations","topic organization","exported conversation files","search results"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_5","uri":"capability://text.generation.language.streaming.response.processing.with.real.time.token.counting.and.progressive.rendering","name":"streaming response processing with real-time token counting and progressive rendering","description":"Cherry Studio implements a Streaming and Message Processing system that handles real-time LLM responses through chunked streaming, with progressive message rendering and live token counting. The system normalizes streaming responses across different providers (OpenAI, Anthropic, etc.) into a unified stream format, enabling consistent UI updates. As tokens arrive, the system updates the UI incrementally, displays token usage in real-time, and handles stream interruption/cancellation. Markdown and code blocks are parsed and rendered progressively, enabling users to see formatted output as it streams.","intents":["Display LLM responses in real-time as they stream from the provider","Track token usage during streaming to monitor API costs","Cancel long-running requests without losing partial responses","Render markdown and code blocks progressively with syntax highlighting"],"best_for":["Developers building responsive chat UIs with streaming LLM responses","Teams monitoring API costs through real-time token counting","Users with slow network connections who benefit from progressive response display"],"limitations":["Token counting is approximate during streaming — final count may differ from provider's actual count","Markdown parsing during streaming may cause re-renders as content updates — no built-in debouncing","Stream cancellation is immediate but may leave partial state in Redux — requires manual cleanup","Provider-specific streaming formats require custom normalization logic per provider"],"requires":["LLM provider with streaming API support","Network connection with streaming capability","React component library for progressive rendering"],"input_types":["streaming response chunks","provider-specific stream formats"],"output_types":["normalized stream events","rendered UI updates","token usage metrics","formatted markdown/code blocks"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_6","uri":"capability://tool.use.integration.model.context.protocol.mcp.server.management.with.tool.discovery.and.execution","name":"model context protocol (mcp) server management with tool discovery and execution","description":"Cherry Studio implements a comprehensive MCP Architecture that manages MCP server lifecycle (startup, shutdown, health checks), discovers available tools and resources from connected servers, and executes tools with request/response handling. The MCP Server Management system maintains connections to multiple MCP servers, handles server configuration (local or remote), and manages authentication. MCP Tools and Execution provides a unified interface for invoking tools across different servers, with error handling and timeout management. MCP Prompts and Resources enable servers to inject structured context (prompts, file resources) into agent reasoning.","intents":["Connect to local or remote MCP servers to extend agent capabilities","Discover available tools from MCP servers without manual configuration","Execute tools with automatic request/response serialization","Inject MCP resources and prompts into agent context for better reasoning"],"best_for":["Developers extending Cherry Studio with custom tools via MCP servers","Teams building tool ecosystems that multiple agents can consume","Organizations standardizing on MCP for tool integration across AI applications"],"limitations":["MCP server discovery is manual — requires explicit server configuration in settings","Tool execution is synchronous — no built-in support for long-running async tools","Server health checks are periodic — may not detect failures immediately","No built-in MCP server authentication beyond basic credential storage"],"requires":["MCP servers running and accessible (local or remote)","MCP server configuration with host/port or command","Network connectivity to MCP servers","Proper firewall rules for remote MCP server access"],"input_types":["MCP server configuration","tool invocation requests","tool parameters"],"output_types":["tool schemas (JSON)","tool execution results","MCP resources and prompts","server health status"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_7","uri":"capability://code.generation.editing.code.execution.and.analysis.with.openclaw.integration.and.syntax.highlighting","name":"code execution and analysis with openclaw integration and syntax highlighting","description":"Cherry Studio integrates code execution capabilities through OpenClaw (a code execution sandbox) and provides syntax-aware code analysis. The Code Tools system enables agents to execute code snippets in isolated environments, with output capture and error handling. Code blocks in chat are rendered with syntax highlighting for 40+ languages, with copy-to-clipboard and execution buttons. The system maintains code execution history and enables debugging through output inspection. Integration with MCP tools enables code execution across multiple languages (Python, JavaScript, Shell, etc.).","intents":["Execute code snippets from chat responses in isolated sandboxes","Debug code by inspecting execution output and error messages","Render code blocks with syntax highlighting and language detection","Build agents that can write and execute code autonomously"],"best_for":["Developers using AI to write and test code interactively","Data scientists executing analysis code from chat","Teams building autonomous coding agents"],"limitations":["Code execution is sandboxed but not fully isolated — resource limits may not prevent DoS attacks","Execution timeout is fixed — no per-language optimization for long-running code","Output capture is limited to stdout/stderr — no access to file system modifications","Syntax highlighting is client-side only — no semantic analysis or linting"],"requires":["OpenClaw or equivalent code execution service configured","Network connectivity to code execution service","Proper sandboxing/containerization for security"],"input_types":["code snippets","programming language specification","execution parameters"],"output_types":["execution results","error messages","rendered code blocks with syntax highlighting"],"categories":["code-generation-editing","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_8","uri":"capability://search.retrieval.web.search.integration.with.real.time.information.retrieval.and.source.attribution","name":"web search integration with real-time information retrieval and source attribution","description":"Cherry Studio integrates web search capabilities that enable agents and assistants to retrieve real-time information from the internet. The Web Search Settings configure search provider (Google, Bing, etc.) and enable/disable search per assistant. When web search is enabled, agents can invoke search tools to find current information, with results including source URLs and snippets. Search results are injected into the LLM context, enabling responses grounded in current web information. The system handles search result ranking and deduplication.","intents":["Retrieve current information (news, prices, events) not in LLM training data","Ground agent responses in web sources with attribution","Enable assistants to answer questions about recent events","Build research agents that can search the web autonomously"],"best_for":["Researchers needing current information in AI responses","Customer service agents answering questions about real-time data","News/content creation assistants requiring up-to-date information"],"limitations":["Web search results are limited to configured search provider — no multi-source search aggregation","Search result quality depends on provider ranking — no built-in result filtering or verification","Search latency adds to response time — no caching of search results across conversations","Source attribution is URL-only — no automatic fact-checking or credibility scoring"],"requires":["Web search provider API key (Google, Bing, etc.)","Network connectivity to search provider","Web Search Settings configured in application"],"input_types":["search queries","search provider configuration"],"output_types":["search results with URLs and snippets","ranked result list","injected context for LLM"],"categories":["search-retrieval","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-cherryhq--cherry-studio__cap_9","uri":"capability://automation.workflow.electron.multi.process.architecture.with.ipc.communication.and.state.synchronization","name":"electron multi-process architecture with ipc communication and state synchronization","description":"Cherry Studio is built on Electron's multi-process architecture, separating the main process (privileged operations) from renderer processes (UI). The IPC Communication System provides bidirectional message passing between main and renderer processes using a channel-based architecture defined in IpcChannel.ts. State Management with Redux maintains application state in the renderer process, with persistence to the local database via main process IPC calls. The architecture enables responsive UI by offloading heavy operations (file I/O, API calls, database queries) to the main process.","intents":["Build responsive desktop UI without blocking on I/O operations","Persist application state to local database with automatic synchronization","Manage privileged operations (file system access, system integration) in main process","Enable hot-reload and development workflows with Electron Vite"],"best_for":["Desktop application developers building complex AI tools","Teams requiring local-first architecture with offline capability","Developers familiar with Electron and React ecosystems"],"limitations":["IPC communication adds latency (~5-10ms per round-trip) — not suitable for high-frequency operations","Redux state is in-memory only — large conversation histories may consume significant memory","Multi-process debugging is complex — requires separate DevTools for main and renderer processes","Electron distribution size is large (~150MB) — not suitable for bandwidth-constrained environments"],"requires":["Node.js 18+","Electron 20+ (specified in package.json)","React 18+ for renderer process","SQLite or equivalent for local database"],"input_types":["IPC messages","Redux actions","database queries"],"output_types":["IPC responses","Redux state updates","persisted data"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":55,"verified":false,"data_access_risk":"high","permissions":["API keys for at least one LLM provider (OpenAI, Anthropic, DeepSeek, etc.)","Network connectivity to provider endpoints","TypeScript/Node.js runtime for local API server","MCP servers configured and running (local or remote)","LLM provider with function-calling support (OpenAI, Anthropic, etc.)","Node.js 18+ for local tool execution","Proper file system permissions for code execution tools","Local API server enabled in settings","Network access to local machine (localhost or LAN)","OAuth provider configuration (optional)"],"failure_modes":["Provider-specific parameter differences may not be fully normalized — some advanced parameters only work with specific providers","Streaming response latency varies by provider; no built-in response time optimization across providers","API key management is local-only — no centralized key rotation service for enterprise deployments","Agent reasoning latency compounds with each tool call — no built-in optimization for reducing reasoning steps","Tool execution is sequential; no parallel tool invocation support","MCP server lifecycle management is local-only — no distributed agent execution across machines","Agent state is stored in Redux; no built-in persistence layer for long-running agents across application restarts","Local API server is not production-grade — no rate limiting or DDoS protection","OAuth integration is basic — no support for advanced flows (PKCE, device flow)","LAN transfer is limited to local network — no support for remote transfer","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.8143576514407512,"quality":0.5,"ecosystem":0.6000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.549Z","last_scraped_at":"2026-05-03T13:57:04.027Z","last_commit":"2026-05-03T08:21:03Z"},"community":{"stars":44942,"forks":4273,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=cherryhq--cherry-studio","compare_url":"https://unfragile.ai/compare?artifact=cherryhq--cherry-studio"}},"signature":"0CtGEXMt1YHqx3lVMMbtPEBIeT3Kr5qB6jtiRWSre3tn7dI+6C1JmhwjLfXBsUwjJF1IzqiYfaXyP/QNrhYQAw==","signedAt":"2026-06-20T23:49:50.076Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/cherryhq--cherry-studio","artifact":"https://unfragile.ai/cherryhq--cherry-studio","verify":"https://unfragile.ai/api/v1/verify?slug=cherryhq--cherry-studio","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}