{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-echarts","slug":"echarts","name":"ECharts","type":"mcp","url":"https://github.com/hustcc/mcp-echarts","page_url":"https://unfragile.ai/echarts","categories":["data-analysis"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-echarts__cap_0","uri":"capability://tool.use.integration.mcp.based.chart.generation.tool.registration.and.routing","name":"mcp-based chart generation tool registration and routing","description":"Implements a factory pattern using @modelcontextprotocol/sdk to register 17 specialized chart generation tools as MCP-compliant endpoints. The McpServer instance manages tool discovery, input validation schemas, and request routing across multiple transport protocols (stdio, SSE, HTTP). Each tool is registered with Zod-based input schemas that enforce type safety before chart generation pipelines execute.","intents":["I want to expose chart generation capabilities to AI assistants via the Model Context Protocol","I need to register multiple chart tools with consistent input validation and error handling","I want to support multiple client types (desktop, web, API) through a single server implementation"],"best_for":["AI assistant developers integrating visualization into Claude, VSCode, or custom LLM applications","Teams building MCP servers that need production-ready tool registration patterns","Developers requiring multi-transport protocol support (stdio for desktop, SSE/HTTP for web)"],"limitations":["Tool registration is static at server startup — dynamic tool addition requires server restart","Session management for SSE and HTTP protocols relies on in-memory maps, not persistent storage","No built-in authentication or rate limiting at the MCP protocol layer"],"requires":["@modelcontextprotocol/sdk ^1.12.0","Node.js 18+","TypeScript 4.5+ for type safety"],"input_types":["JSON tool parameters matching Zod schemas","Chart configuration objects with data and styling"],"output_types":["MCP tool definitions with input/output schemas","Chart images (PNG, SVG) or ECharts option JSON"],"categories":["tool-use-integration","mcp-protocol"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_1","uri":"capability://tool.use.integration.multi.transport.protocol.bridging.stdio.sse.http","name":"multi-transport protocol bridging (stdio, sse, http)","description":"Implements three transport protocol handlers that allow the same MCP server instance to serve desktop applications (stdio), web clients (SSE with sessionId), and API services (HTTP with mcp-session-id headers). Each protocol maintains separate session maps for stateful chart generation workflows, with automatic fallback mechanisms for connection failures.","intents":["I want to run the same chart server for Claude desktop, web browsers, and REST API clients","I need real-time streaming of chart generation progress to web applications","I want stateless HTTP integration for serverless or containerized deployments"],"best_for":["Teams deploying mcp-echarts across multiple client environments (desktop, web, mobile)","Developers building AI assistants that need to work in Claude, VSCode, and custom web UIs","Organizations requiring both synchronous REST APIs and streaming MCP connections"],"limitations":["Session state is in-memory only — server restart loses all active sessions","SSE connections require persistent TCP connections, not suitable for high-latency networks","HTTP protocol requires mcp-session-id header management on client side","No built-in load balancing or session migration across multiple server instances"],"requires":["Node.js 18+ with streaming support","For SSE: browser or client with EventSource API support","For HTTP: standard HTTP/1.1 or HTTP/2 client library"],"input_types":["stdio: JSON-RPC messages via stdin","SSE: POST requests with sessionId query parameter","HTTP: POST requests with mcp-session-id header"],"output_types":["stdio: JSON-RPC responses via stdout","SSE: Server-sent events with chart data","HTTP: JSON responses with chart image URLs or Base64 data"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_10","uri":"capability://automation.workflow.batch.chart.generation.with.session.based.state.management","name":"batch chart generation with session-based state management","description":"Manages stateful chart generation workflows across multiple requests using session maps (for SSE and HTTP protocols). Sessions maintain context across multiple chart generation calls, enabling workflows where one chart's output feeds into the next chart's input. Session state includes generated chart data, configuration history, and intermediate results.","intents":["I want to generate multiple related charts in sequence with shared context","I need to maintain state across multiple chart generation requests in a single user session","I want to enable iterative chart refinement where each request builds on previous results"],"best_for":["Interactive chart generation workflows in web applications","Multi-step data analysis pipelines where charts depend on previous results","Conversational AI assistants that generate multiple charts in a single conversation"],"limitations":["Session state is in-memory only — lost on server restart","No automatic session cleanup; old sessions accumulate in memory","Session isolation is not enforced; no built-in access control between sessions","Scaling to multiple server instances requires external session store (Redis, etc.)","No session persistence or recovery mechanisms"],"requires":["SSE or HTTP protocol (stdio is stateless)","Session ID management on client side (sessionId for SSE, mcp-session-id header for HTTP)"],"input_types":["Chart generation requests with optional sessionId","Session context data from previous requests"],"output_types":["Chart images with session context","Session state snapshots for client-side caching"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_11","uri":"capability://automation.workflow.zero.dependency.chart.rendering.with.local.canvas.execution","name":"zero-dependency chart rendering with local canvas execution","description":"Renders charts entirely locally using Node.js canvas and SVG engines without external service dependencies. The rendering pipeline executes ECharts JavaScript in a Node.js context with canvas bindings, eliminating the need for browser instances, external rendering services, or cloud APIs. All rendering happens in-process with no network calls.","intents":["I want to generate charts without depending on external rendering services","I need fast chart rendering with no network latency","I want to avoid browser overhead and licensing costs of headless browser services"],"best_for":["Self-contained deployments with no external service dependencies","High-throughput chart generation where latency is critical","Environments where external service calls are restricted or unreliable"],"limitations":["Rendering performance depends on Node.js canvas implementation, which may be slower than browser engines","Canvas rendering requires native module compilation, which can fail on some platforms","No support for advanced browser features (WebGL, complex CSS) in canvas rendering","Memory usage scales with chart complexity; no garbage collection between renders","SVG rendering is slower than PNG for very complex charts"],"requires":["Node.js 18+ with native module support","node-canvas or equivalent (may require system dependencies: libcairo, libpixman, etc.)","No external services required"],"input_types":["ECharts option objects"],"output_types":["PNG image buffers","SVG strings"],"categories":["automation-workflow","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_12","uri":"capability://data.processing.analysis.dynamic.chart.configuration.composition.from.ai.generated.parameters","name":"dynamic chart configuration composition from ai-generated parameters","description":"Accepts AI-generated chart parameters (data, styling, chart type, axes configuration) and composes them into valid ECharts option objects through a transformation pipeline. The pipeline validates inputs using Zod schemas, applies default styling, merges user-provided options with defaults, and produces complete ECharts configurations ready for rendering.","intents":["I want to convert AI-generated chart descriptions into executable chart configurations","I need to handle incomplete or partial chart specifications from LLM outputs","I want to apply consistent styling and defaults across all AI-generated charts"],"best_for":["AI assistants that generate chart specifications in natural language or structured format","Applications where LLM outputs need to be transformed into valid chart configurations","Systems requiring consistent styling across dynamically generated charts"],"limitations":["Composition logic is fixed; no dynamic composition strategies","Default styling may not match user preferences; requires customization","Complex chart configurations may exceed composition capabilities","No validation of semantic correctness (e.g., data type mismatches between data and axes)"],"requires":["Chart parameters matching Zod schemas","ECharts 5.0+ option structure knowledge"],"input_types":["Partial chart configurations from AI models","Chart type specifications","Data arrays and styling options"],"output_types":["Complete ECharts option objects","Validated chart configurations"],"categories":["data-processing-analysis","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_2","uri":"capability://data.processing.analysis.zod.based.schema.validation.for.chart.inputs","name":"zod-based schema validation for chart inputs","description":"Implements type-safe input validation using Zod schemas across all 17 chart generation tools. Each tool defines a Zod schema that validates data types, array structures, numeric ranges, and required fields before the data reaches the ECharts rendering pipeline. Validation errors are caught early and returned as structured error messages to the MCP client.","intents":["I want to ensure chart data is valid before expensive rendering operations","I need to provide clear error messages when AI models generate malformed chart configurations","I want type safety without runtime type checking overhead"],"best_for":["Teams using AI models to generate chart configurations and needing input guardrails","Developers building MCP tools that require strict input validation","Projects where invalid data could cause rendering failures or security issues"],"limitations":["Zod validation adds ~5-10ms per tool invocation for complex schemas","Schema definitions must be maintained manually as chart types evolve","No automatic schema generation from ECharts option types — schemas are hand-written"],"requires":["zod ^3.0.0 or compatible","TypeScript for schema type inference"],"input_types":["JSON objects matching ECharts chart option structures","Arrays of data points with numeric, string, or categorical values"],"output_types":["Validated chart configuration objects","Zod validation errors with field-level details"],"categories":["data-processing-analysis","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_3","uri":"capability://image.visual.financial.and.trading.chart.generation.candlestick.ohlc.technical.indicators","name":"financial and trading chart generation (candlestick, ohlc, technical indicators)","description":"Generates specialized financial charts including candlestick, OHLC (open-high-low-close), and technical indicator overlays using ECharts' financial chart components. Accepts time-series OHLC data, volume information, and technical indicator arrays (moving averages, Bollinger Bands, RSI), then transforms them into ECharts option objects with proper axis scaling, legend management, and interactive tooltips.","intents":["I want to visualize stock price movements with candlestick charts from AI-generated trading data","I need to overlay technical indicators (moving averages, RSI) on price charts","I want to display volume bars alongside price candlesticks"],"best_for":["Financial data analysis platforms integrating AI-powered chart generation","Trading dashboards that need dynamic chart updates from LLM-generated analysis","Fintech applications where AI models interpret market data and visualize insights"],"limitations":["No real-time data streaming — charts are static snapshots of provided data","Technical indicator calculations must be pre-computed by the caller; server only renders","Limited to ECharts' financial chart capabilities; advanced derivatives or exotic indicators require custom implementation","No built-in support for multiple timeframes or automatic resampling"],"requires":["OHLC data with timestamp, open, high, low, close, volume fields","ECharts 5.0+ for financial chart components","Node.js 18+ with canvas rendering support"],"input_types":["OHLC data arrays: [{timestamp, open, high, low, close, volume}, ...]","Technical indicator arrays: [{timestamp, value}, ...]","Chart styling options: colors, axis labels, legend configuration"],"output_types":["PNG images of candlestick charts","SVG vector graphics for web embedding","ECharts option JSON for client-side rendering"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_4","uri":"capability://image.visual.statistical.and.analytical.chart.generation.histograms.box.plots.scatter.plots","name":"statistical and analytical chart generation (histograms, box plots, scatter plots)","description":"Generates statistical visualization charts including histograms, box plots, scatter plots, and distribution curves. Accepts raw data arrays or pre-computed statistical summaries, performs binning/aggregation if needed, and renders charts with statistical annotations (quartiles, outliers, trend lines). Supports both univariate and bivariate statistical visualizations.","intents":["I want to visualize data distributions and outliers from AI-analyzed datasets","I need to compare statistical properties across multiple data groups","I want to display correlation relationships in scatter plots with trend lines"],"best_for":["Data science and analytics platforms where AI models generate statistical insights","Research dashboards that need dynamic statistical visualizations","Business intelligence tools integrating LLM-powered data analysis"],"limitations":["Statistical calculations (quartiles, outliers, trend lines) must be pre-computed; server only renders","No automatic outlier detection — outliers must be marked by the caller","Limited to univariate and bivariate analysis; multivariate statistical charts require custom implementation","Binning strategies for histograms are fixed; no adaptive binning algorithms"],"requires":["Numeric data arrays for univariate analysis","Paired data arrays for bivariate scatter plots","Optional: pre-computed statistical summaries (mean, median, quartiles)"],"input_types":["Numeric arrays: [value1, value2, ...]","Paired data: [{x, y}, ...]","Statistical summaries: {min, q1, median, q3, max, outliers}"],"output_types":["PNG histogram, box plot, or scatter plot images","SVG vector graphics with statistical annotations","ECharts option JSON with statistical overlays"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_5","uri":"capability://image.visual.basic.chart.type.generation.line.bar.pie.area.charts","name":"basic chart type generation (line, bar, pie, area charts)","description":"Generates fundamental chart types including line charts, bar charts (vertical and horizontal), pie charts, and area charts. Accepts simple data arrays or category-value pairs, applies styling options (colors, labels, legends), and renders through the ECharts rendering pipeline. Supports stacked variants and multi-series compositions.","intents":["I want to quickly visualize simple datasets as line or bar charts","I need to create pie charts showing categorical breakdowns","I want to display time-series data with area charts"],"best_for":["General-purpose data visualization in AI assistants and dashboards","Quick prototyping of chart visualizations from AI-generated data","Applications requiring standard chart types without specialized statistical features"],"limitations":["No automatic axis scaling optimization — caller must provide appropriate data ranges","Limited customization compared to direct ECharts API usage","No built-in data aggregation or grouping — data must be pre-processed","Stacking behavior is fixed; no dynamic stacking mode switching"],"requires":["Simple data arrays or category-value pairs","ECharts 5.0+ for rendering"],"input_types":["Simple arrays: [value1, value2, ...]","Category-value pairs: [{category, value}, ...]","Multi-series data: [{name, data: [...]}, ...]"],"output_types":["PNG chart images","SVG vector graphics","ECharts option JSON"],"categories":["image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_6","uri":"capability://image.visual.server.side.chart.rendering.to.png.and.svg.formats","name":"server-side chart rendering to png and svg formats","description":"Renders ECharts option objects to PNG and SVG image formats using Node.js canvas and SVG rendering engines. The rendering pipeline converts ECharts JavaScript options to visual output without requiring a browser, using headless rendering with configurable dimensions, DPI, and color profiles. Supports both raster (PNG) and vector (SVG) output formats.","intents":["I want to generate chart images server-side without spinning up a browser","I need to export charts as PNG for embedding in documents or emails","I want SVG output for web embedding with scalability"],"best_for":["Server-side chart generation in Node.js applications","Batch chart rendering for reports or dashboards","AI assistants that need to return chart images to users"],"limitations":["Rendering adds ~200-500ms per chart depending on complexity and output format","Canvas rendering requires native dependencies (node-canvas) which may have platform-specific build issues","SVG rendering is slower than PNG for complex charts with many data points","No support for interactive features in output images — only static visualizations","Memory usage scales with chart complexity; very large datasets may cause OOM errors"],"requires":["Node.js 18+ with native module support","node-canvas or equivalent for PNG rendering","ECharts 5.0+ with rendering support"],"input_types":["ECharts option objects (JavaScript/JSON)","Rendering configuration: {width, height, dpi, format}"],"output_types":["PNG image buffers (raster)","SVG strings (vector)","Base64-encoded image data"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_7","uri":"capability://automation.workflow.minio.object.storage.integration.with.base64.fallback","name":"minio object storage integration with base64 fallback","description":"Persists generated chart images to MinIO-compatible object storage (S3, MinIO, etc.) with automatic fallback to Base64 encoding when storage is unavailable. The image handler in src/utils/imageHandler.ts detects MinIO configuration, uploads PNG/SVG images to the configured bucket, and returns either object URLs or Base64-encoded data URIs depending on storage availability.","intents":["I want to store generated charts in object storage for long-term persistence","I need chart URLs that can be shared or embedded in external applications","I want automatic fallback to Base64 encoding if object storage is unavailable"],"best_for":["Production deployments requiring persistent chart storage","Multi-instance deployments where charts need to be accessible across servers","Applications that need to share chart URLs with external users"],"limitations":["MinIO integration adds ~100-300ms latency per chart upload","Base64 fallback increases response payload size by ~33% compared to URLs","No built-in cleanup or retention policies for old charts","Requires MinIO credentials and bucket configuration at startup","No support for private/signed URLs — all uploaded charts are publicly accessible by default"],"requires":["MinIO server or S3-compatible storage (optional; Base64 fallback works without it)","MinIO credentials: MINIO_ENDPOINT, MINIO_ACCESS_KEY, MINIO_SECRET_KEY, MINIO_BUCKET","Network access to MinIO server if configured"],"input_types":["PNG or SVG image buffers","Chart metadata: filename, content-type"],"output_types":["MinIO object URL: https://minio.example.com/bucket/chart-uuid.png","Base64 data URI: data:image/png;base64,iVBORw0KGgo..."],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_8","uri":"capability://data.processing.analysis.echarts.option.json.export.for.client.side.rendering","name":"echarts option json export for client-side rendering","description":"Exports generated chart configurations as ECharts option JSON objects that can be rendered client-side using the ECharts JavaScript library. The chart generation tools produce ECharts-compatible option objects that include data, styling, axes, legends, and interactive features, enabling clients to render charts in browsers without server-side image generation.","intents":["I want to send chart configurations to web clients for interactive rendering","I need to enable client-side chart customization after server-side generation","I want to reduce server load by offloading rendering to the client"],"best_for":["Web applications where clients have ECharts library available","Interactive dashboards that need client-side chart manipulation","Scenarios where bandwidth is more constrained than CPU (prefer JSON over images)"],"limitations":["Client must have ECharts library loaded and configured","JSON payloads can be large for complex charts with many data points","No guarantee of consistent rendering across different ECharts versions","Interactive features depend on client-side ECharts implementation"],"requires":["ECharts 5.0+ on the client side","JavaScript runtime in the client environment"],"input_types":["Chart generation parameters (data, styling, chart type)"],"output_types":["ECharts option JSON objects","Serialized JSON strings for transmission"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-echarts__cap_9","uri":"capability://image.visual.specialized.visualization.tools.heatmaps.gauges.sankey.diagrams","name":"specialized visualization tools (heatmaps, gauges, sankey diagrams)","description":"Generates specialized chart types including heatmaps for matrix data, gauge charts for metric visualization, and Sankey diagrams for flow analysis. Each specialized tool handles data transformation specific to its chart type (matrix normalization for heatmaps, metric scaling for gauges, node-link conversion for Sankey) and produces ECharts options with appropriate styling and interactivity.","intents":["I want to visualize correlation matrices or time-series heatmaps","I need to display KPI metrics with gauge charts","I want to show data flow or process relationships with Sankey diagrams"],"best_for":["Data analysis dashboards requiring specialized visualizations","Business intelligence platforms with KPI monitoring","Process analysis and flow visualization applications"],"limitations":["Heatmap rendering can be slow for matrices larger than 100x100 due to cell count","Gauge charts are limited to single metrics; no multi-gauge layouts","Sankey diagrams require pre-computed node and link structures; no automatic layout","No built-in color scale optimization for heatmaps — caller must provide color mapping"],"requires":["Heatmap: 2D numeric matrix data","Gauge: single numeric value with min/max bounds","Sankey: node array and link array with source/target indices"],"input_types":["Heatmap: [[value, ...], ...] matrix","Gauge: {value, min, max, name}","Sankey: {nodes: [{name}, ...], links: [{source, target, value}, ...]}"],"output_types":["PNG/SVG heatmap images","Gauge chart visualizations","Sankey diagram visualizations","ECharts option JSON for all types"],"categories":["image-visual","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":33,"verified":false,"data_access_risk":"moderate","permissions":["@modelcontextprotocol/sdk ^1.12.0","Node.js 18+","TypeScript 4.5+ for type safety","Node.js 18+ with streaming support","For SSE: browser or client with EventSource API support","For HTTP: standard HTTP/1.1 or HTTP/2 client library","SSE or HTTP protocol (stdio is stateless)","Session ID management on client side (sessionId for SSE, mcp-session-id header for HTTP)","Node.js 18+ with native module support","node-canvas or equivalent (may require system dependencies: libcairo, libpixman, etc.)"],"failure_modes":["Tool registration is static at server startup — dynamic tool addition requires server restart","Session management for SSE and HTTP protocols relies on in-memory maps, not persistent storage","No built-in authentication or rate limiting at the MCP protocol layer","Session state is in-memory only — server restart loses all active sessions","SSE connections require persistent TCP connections, not suitable for high-latency networks","HTTP protocol requires mcp-session-id header management on client side","No built-in load balancing or session migration across multiple server instances","Session state is in-memory only — lost on server restart","No automatic session cleanup; old sessions accumulate in memory","Session isolation is not enforced; no built-in access control between sessions","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.5,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.6,"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":"2026-06-17T09:51:03.038Z","last_scraped_at":"2026-05-03T14:00:15.503Z","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=echarts","compare_url":"https://unfragile.ai/compare?artifact=echarts"}},"signature":"+DZsi0nc9cnBtKqRVR5atuAqYTQFRH21lAlxdEFAGsx1IndPLc+v/H9t/K6yvV0F0xaIi3EkuMYaT7Pb8MD9CA==","signedAt":"2026-06-20T06:55:42.306Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/echarts","artifact":"https://unfragile.ai/echarts","verify":"https://unfragile.ai/api/v1/verify?slug=echarts","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"}}