{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_dappergpt","slug":"dappergpt","name":"DapperGPT","type":"extension","url":"https://dappergpt.com","page_url":"https://unfragile.ai/dappergpt","categories":["app-builders"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_dappergpt__cap_0","uri":"capability://tool.use.integration.multi.provider.llm.model.switching.with.unified.interface","name":"multi-provider llm model switching with unified interface","description":"Provides a single chat interface that abstracts away provider-specific API differences, allowing users to switch between OpenAI GPT, Anthropic Claude, Google Gemini, Mistral, Grok, and Llama by selecting from a dropdown and providing their own API keys. The interface normalizes request/response handling across providers with different tokenization, rate limits, and response formats, eliminating the need to maintain separate tabs or applications for each model.","intents":["I want to compare responses from multiple LLM providers without switching applications","I need to use different models for different tasks but don't want to manage multiple interfaces","I want to bring my own API keys and avoid vendor lock-in to a single provider"],"best_for":["AI researchers and prompt engineers evaluating model outputs across providers","Teams with existing API keys across multiple providers seeking unified access","Cost-conscious builders wanting to switch providers based on price/performance tradeoffs"],"limitations":["No built-in cost tracking across providers — users must monitor billing separately with each provider","Model version selection appears limited to provider defaults — no explicit version pinning documented","Switching models mid-conversation requires manual context re-entry; no automatic context migration between providers","API key storage security model undocumented — unclear if keys are encrypted at rest or stored server-side"],"requires":["Valid API key for at least one supported provider (OpenAI, Anthropic, Google, Mistral, Grok, or Llama)","Modern web browser with JavaScript enabled","Network connectivity to provider APIs"],"input_types":["text prompts","file uploads (types/sizes unspecified)","images"],"output_types":["text responses","structured data (model-dependent)"],"categories":["tool-use-integration","multi-provider-abstraction"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_1","uri":"capability://memory.knowledge.persistent.conversation.storage.with.full.text.search.and.retrieval","name":"persistent conversation storage with full-text search and retrieval","description":"Stores all chat conversations server-side (security model unspecified) and indexes them for Spotlight-like full-text search, allowing users to retrieve past interactions by keyword without scrolling through history. The search appears to index both user prompts and AI responses, enabling discovery of relevant conversations across sessions. Conversations can be organized into folders and pinned for quick access.","intents":["I want to find a specific conversation I had weeks ago without manually scrolling through history","I need to organize my conversations by project or topic for easy retrieval","I want to build a searchable knowledge base from my ChatGPT interactions"],"best_for":["Researchers and knowledge workers who accumulate hundreds of conversations and need retrieval","Remote workers using ChatGPT for ongoing projects requiring historical context lookup","Teams wanting to preserve institutional knowledge from AI interactions"],"limitations":["Search algorithm/indexing strategy not documented — unclear if semantic search or keyword-only","No documented data retention policy — unclear how long conversations are stored or if deletion is permanent","Folder organization is manual — no automatic tagging or categorization based on conversation content","Search scope limited to user's own conversations — no cross-user or shared conversation search","No bulk export or backup mechanism documented for conversation data"],"requires":["DapperGPT account with active session","At least one completed conversation to search","Network connectivity to DapperGPT servers"],"input_types":["search queries (text)"],"output_types":["conversation summaries","full conversation threads","metadata (date, model used, folder)"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_2","uri":"capability://data.processing.analysis.file.and.image.upload.with.multi.modal.context.injection","name":"file and image upload with multi-modal context injection","description":"Accepts file uploads (types and size limits unspecified) and image uploads, injecting their content or visual information into the chat context before sending requests to the selected LLM provider. The system appears to handle file parsing and image encoding transparently, allowing users to reference documents, code, or images in prompts without manual copy-paste. Implementation details for file type support and preprocessing are undocumented.","intents":["I want to upload a PDF or document and ask questions about its content","I need to share code snippets or images with the AI without pasting them manually","I want to analyze images or documents using vision-capable models like GPT-4V or Claude"],"best_for":["Developers debugging code by uploading error logs or source files","Researchers analyzing papers or documents with AI assistance","Content creators using vision models for image analysis or generation"],"limitations":["Supported file types not documented — unclear which formats (PDF, DOCX, TXT, etc.) are supported","File size limits not specified — may cause failures with large documents","File preprocessing strategy unknown — unclear if OCR is applied to PDFs or if raw text extraction is used","Image encoding/compression not documented — may affect vision model accuracy","No batch upload capability mentioned — single file per interaction implied","Uploaded files may be stored server-side; retention policy undocumented"],"requires":["DapperGPT web interface access","File or image in a supported format (unspecified)","LLM provider that supports the content type (e.g., vision-capable model for images)"],"input_types":["files (types unspecified)","images (formats unspecified)"],"output_types":["text analysis","structured extraction","code suggestions"],"categories":["data-processing-analysis","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_3","uri":"capability://text.generation.language.custom.prompt.management.and.reusable.prompt.templates","name":"custom prompt management and reusable prompt templates","description":"Allows users to create, save, and reuse custom prompts as templates that can be applied to new conversations. Prompts appear to be stored per-user and can be selected from a dropdown or menu before initiating a chat. This enables rapid iteration on prompt engineering without re-typing complex instructions for recurring tasks.","intents":["I want to save my best prompts and reuse them across conversations","I need to maintain consistent prompt structure for a specific task (e.g., code review, summarization)","I want to build a library of prompts for my team to use"],"best_for":["Prompt engineers and AI practitioners refining and reusing effective prompts","Teams with standardized workflows that benefit from consistent prompt templates","Power users who iterate frequently on prompt wording"],"limitations":["Prompt versioning not mentioned — no history of prompt edits or rollback capability","No prompt sharing mechanism documented — templates appear to be per-user only","No prompt performance metrics or A/B testing tools mentioned","Prompt organization (folders, tags) not documented — unclear how users manage large prompt libraries","No prompt variable substitution or parameterization mentioned — templates may be static"],"requires":["DapperGPT account","At least one saved custom prompt"],"input_types":["prompt text with instructions"],"output_types":["saved prompt template","prompt metadata (name, description)"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_4","uri":"capability://tool.use.integration.chrome.extension.for.in.browser.ai.access.with.context.integration","name":"chrome extension for in-browser ai access with context integration","description":"A Chrome extension (currently marked 'available soon' — not yet production-ready) that brings DapperGPT's chat interface to any website, allowing users to leverage AI capabilities without leaving their current browser context. The specific integration pattern (sidebar, overlay, context menu) is undocumented, as is the mechanism for capturing page context (selected text, DOM content, page metadata). Extension will likely use Chrome's extension APIs for content script injection and message passing.","intents":["I want to ask ChatGPT about the content on the current webpage without opening a new tab","I need to quickly summarize or analyze text on a webpage using AI","I want to use AI assistance while researching without context-switching"],"best_for":["Remote workers and researchers who want seamless AI access during browsing","Content creators analyzing web content without tab-switching","Developers debugging web applications with AI assistance"],"limitations":["Extension is pre-release ('available soon') — not yet available for testing or production use","Specific integration pattern (sidebar vs. overlay vs. context menu) undocumented","Page context capture mechanism unknown — unclear if extension can access DOM, selected text, or page metadata","Sandboxing/permission model undocumented — unclear what page data the extension can access","No documentation on extension conflicts with other tools or performance impact","Chrome-only support stated — no Firefox, Safari, or Edge support mentioned","Extension permissions and privacy implications not documented"],"requires":["Chrome browser (version unspecified)","DapperGPT account","Extension installation from Chrome Web Store (when released)","Valid API key for at least one LLM provider"],"input_types":["webpage content (mechanism unspecified)","selected text (if supported)","user prompts"],"output_types":["text responses","analysis results"],"categories":["tool-use-integration","browser-extension"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_5","uri":"capability://tool.use.integration.agent.based.interaction.with.tool.and.mcp.integration","name":"agent-based interaction with tool and mcp integration","description":"Supports agent-based AI interactions where the LLM can invoke external tools and services through a Model Context Protocol (MCP) integration or custom toolchain. The system appears to enable 'human-like responses' through agentic loops, though specific tool types, MCP implementation details, and available tools are undocumented. Web browsing and code execution are mentioned as available tools but their implementation is not detailed.","intents":["I want the AI to autonomously search the web and synthesize information into a response","I need the AI to execute code and return results without manual copy-paste","I want to extend DapperGPT with custom tools or integrations"],"best_for":["Developers building AI agents that need external tool access","Researchers requiring web search and code execution capabilities","Teams wanting to integrate custom business logic into AI workflows"],"limitations":["MCP integration specifics undocumented — unclear which MCP servers are supported or how to add custom ones","Available tools not enumerated — only 'web browsing' and 'code execution' mentioned without implementation details","Tool invocation strategy unknown — unclear if tools are called automatically or require user approval","Agent loop configuration not documented — no control over max iterations, timeout, or failure handling","Custom tool development process not documented — unclear how to add proprietary tools","Tool output handling unknown — unclear how tool results are injected back into the conversation","No documentation on tool rate limits or cost implications"],"requires":["DapperGPT account with agent features enabled","LLM provider that supports tool calling (OpenAI, Anthropic, etc.)","MCP server setup (if using custom tools — process undocumented)"],"input_types":["text prompts with implicit tool requirements"],"output_types":["text responses with tool-generated data","web search results","code execution output"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_6","uri":"capability://automation.workflow.conversation.pinning.and.folder.based.organization","name":"conversation pinning and folder-based organization","description":"Allows users to pin frequently-accessed conversations to the top of their conversation list and organize conversations into folders for hierarchical grouping. This provides lightweight project/topic-based organization without requiring tagging or automatic categorization. Pinned conversations appear in a dedicated section for quick access.","intents":["I want to keep my active project conversations easily accessible without scrolling","I need to organize conversations by client, project, or topic for team collaboration","I want to archive old conversations while keeping recent ones visible"],"best_for":["Freelancers and consultants managing conversations across multiple clients","Project managers organizing team conversations by project","Researchers grouping conversations by research topic or experiment"],"limitations":["Folder nesting depth not documented — unclear if multi-level folder hierarchies are supported","No automatic conversation categorization — folders must be created and assigned manually","No folder-level permissions or sharing documented — organization appears to be per-user only","No bulk move or reorganization tools mentioned","Folder search not documented — unclear if search is scoped to a folder or global","No folder templates or presets mentioned"],"requires":["DapperGPT account","At least one conversation to organize"],"input_types":["folder names","conversation selection"],"output_types":["organized conversation list","folder hierarchy"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_7","uri":"capability://tool.use.integration.freemium.access.with.api.key.bring.your.own.model","name":"freemium access with api key bring-your-own model","description":"Offers a freemium tier that allows users to test the DapperGPT interface and features without cost, requiring only a free account creation. Full functionality (multi-provider access, conversation storage, search) is unlocked by providing their own API keys from supported LLM providers. This model eliminates platform-imposed usage limits while maintaining transparent, provider-direct billing — users pay OpenAI, Anthropic, etc. directly rather than through DapperGPT.","intents":["I want to try DapperGPT's interface before committing to a subscription","I want to avoid platform markup on API costs and pay providers directly","I want to use my existing API credits across multiple providers"],"best_for":["Cost-conscious builders wanting to minimize platform overhead","Users with existing API commitments to multiple providers","Teams wanting to avoid vendor lock-in to a single billing platform"],"limitations":["No bundled pricing or volume discounts — users must manage billing with each provider separately","No cost tracking or analytics across providers — users must monitor spending in multiple dashboards","API key security model undocumented — unclear if keys are encrypted or stored server-side","Free tier feature set not clearly documented — unclear what functionality is available without API keys","No usage limits or quotas documented for free tier","Billing disputes require contacting individual providers, not DapperGPT support"],"requires":["Free DapperGPT account (email signup)","Valid API key for at least one supported provider (optional for free tier)"],"input_types":["API keys (text)"],"output_types":["account access","feature unlock"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_dappergpt__cap_8","uri":"capability://text.generation.language.rich.chat.interface.with.conversation.management","name":"rich chat interface with conversation management","description":"Provides a modern chat UI with support for multi-turn conversations, message editing/deletion, conversation forking (implied by conversation management features), and visual formatting of responses. The interface normalizes chat interactions across different LLM providers, handling provider-specific response formatting and streaming. Conversations are persisted server-side and can be resumed across sessions.","intents":["I want a clean, modern interface for chatting with multiple AI models","I need to edit or refine my prompts mid-conversation without starting over","I want to explore alternative response paths by forking conversations"],"best_for":["Users preferring a polished UI over command-line or API-based interactions","Iterative prompt engineers who frequently refine and retry prompts","Teams wanting a consistent interface across different LLM providers"],"limitations":["Conversation forking not explicitly documented — unclear if users can branch conversations","Message editing scope not documented — unclear if edits regenerate downstream responses","No collaborative editing or real-time multi-user conversations mentioned","Response streaming behavior not documented — unclear if responses appear incrementally or all at once","No conversation export formats mentioned (markdown, PDF, etc.)","UI customization options not documented — unclear if users can adjust theme, font size, etc."],"requires":["DapperGPT account","Modern web browser with JavaScript enabled","Valid API key for at least one LLM provider"],"input_types":["text prompts","file uploads","images"],"output_types":["formatted text responses","code blocks","structured data"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":45,"verified":false,"data_access_risk":"high","permissions":["Valid API key for at least one supported provider (OpenAI, Anthropic, Google, Mistral, Grok, or Llama)","Modern web browser with JavaScript enabled","Network connectivity to provider APIs","DapperGPT account with active session","At least one completed conversation to search","Network connectivity to DapperGPT servers","DapperGPT web interface access","File or image in a supported format (unspecified)","LLM provider that supports the content type (e.g., vision-capable model for images)","DapperGPT account"],"failure_modes":["No built-in cost tracking across providers — users must monitor billing separately with each provider","Model version selection appears limited to provider defaults — no explicit version pinning documented","Switching models mid-conversation requires manual context re-entry; no automatic context migration between providers","API key storage security model undocumented — unclear if keys are encrypted at rest or stored server-side","Search algorithm/indexing strategy not documented — unclear if semantic search or keyword-only","No documented data retention policy — unclear how long conversations are stored or if deletion is permanent","Folder organization is manual — no automatic tagging or categorization based on conversation content","Search scope limited to user's own conversations — no cross-user or shared conversation search","No bulk export or backup mechanism documented for conversation data","Supported file types not documented — unclear which formats (PDF, DOCX, TXT, etc.) are supported","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.36666666666666664,"quality":0.7300000000000001,"ecosystem":0.2,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:30.282Z","last_scraped_at":"2026-04-05T13:23:42.552Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=dappergpt","compare_url":"https://unfragile.ai/compare?artifact=dappergpt"}},"signature":"ecBStz1aF8YvNWV3WIkHVUOHjo9b9CMYsY4repkqwmJmnyrSR4NYt+6NrWylKFe515Pg5xEgblUBzgp68PyOCw==","signedAt":"2026-06-20T16:03:59.340Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/dappergpt","artifact":"https://unfragile.ai/dappergpt","verify":"https://unfragile.ai/api/v1/verify?slug=dappergpt","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"}}