MCP Server Chart vs Blueprint Chart
A side-by-side look at the MCP Server Chart and Blueprint Chart MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose MCP Server Chart for data visualization work as a local process; choose Blueprint Chart for data visualization as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose MCP Server Chart when
- You need dedicated capabilities in the Data Visualization domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
generate_area_chart, generate_bar_chart, generate_boxplot_chart.
Choose Blueprint Chart when
- You need dedicated capabilities in the Data Visualization domain.
- You prefer a local stdio subprocess transport.
- You want tools like
validate_dsl, inspect_dsl, recommend_chart_type.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Visualization | Data Visualization |
| Quality signal | 71/100 · Great | 59/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | No auth required | Not declared |
| Pricing | Free | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 4,404 | 0 |
| Directory activity | 9 views 0 installs 0 upvotes | 1 views 0 installs 0 upvotes |
| Tools | 27 | 11 |
| Full listing | View MCP Server Chart | View Blueprint Chart |
Tools & capabilities
MCP Server Chart tools 27
generate_area_chartGenerate a area chart to show data trends under continuous independent variables and observe the overall data trend, such as, displacement = velocity (average or instantaneous) × time: s = v × t. If the x-axis is time (t) and the y-axis is velocity (v) at each moment, an area chart allows you to observe the trend of velocity over time and infer the distance traveled by the area's size.generate_bar_chartGenerate a horizontal bar chart to show data for numerical comparisons among different categories, such as, comparing categorical data and for horizontal comparisons.generate_boxplot_chartGenerate a boxplot chart to show data for statistical summaries among different categories, such as, comparing the distribution of data points across categories.generate_column_chartGenerate a column chart, which are best for comparing categorical data, such as, when values are close, column charts are preferable because our eyes are better at judging height than other visual elements like area or angles.generate_district_mapGenerates regional distribution maps, which are usually used to show the administrative divisions and coverage of a dataset. It is not suitable for showing the distribution of specific locations, such as urban administrative divisions, GDP distribution maps of provinces and cities across the country, etc. This tool is limited to generating data maps within China.generate_dual_axes_chartGenerate a dual axes chart which is a combination chart that integrates two different chart types, typically combining a bar chart with a line chart to display both the trend and comparison of data, such as, the trend of sales and profit over time.generate_fishbone_diagramGenerate a fishbone diagram chart to uses a fish skeleton, like structure to display the causes or effects of a core problem, with the problem as the fish head and the causes/effects as the fish bones. It suits problems that can be split into multiple related factors.generate_flow_diagramGenerate a flow diagram chart to show the steps and decision points of a process or system, such as, scenarios requiring linear process presentation.generate_funnel_chartGenerate a funnel chart to visualize the progressive reduction of data as it passes through stages, such as, the conversion rates of users from visiting a website to completing a purchase.generate_histogram_chartGenerate a histogram chart to show the frequency of data points within a certain range. It can observe data distribution, such as, normal and skewed distributions, and identify data concentration areas and extreme points.generate_line_chartGenerate a line chart to show trends over time, such as, the ratio of Apple computer sales to Apple's profits changed from 2000 to 2016.generate_liquid_chartGenerate a liquid chart to visualize a single value as a percentage, such as, the current occupancy rate of a reservoir or the completion percentage of a project.- +15 more on the listing page
Blueprint Chart tools 11
validate_dslParse and semantically validate a .bpc source. Returns { valid, errors[], warnings[] }. Errors include unknown chart types, unknown properties, and empty data blocks with nearest-neighbour suggestions.inspect_dslParse a .bpc source and return a structured summary: chartType, scenes, data (rowCount, entryCount, labels, seriesNames, multiSeries), annotation/colorize/highlight/area-fill presence flags, series count.recommend_chart_typeStart here before writing any .bpc. Takes column types, row count, and the user's goal (a prose sentence — it determines the chart family: comparison/ranking/part-to-whole/composition-over-time/trend/range). Returns ranked chart-type recommendations plus guidance.renderRender a .bpc source to SVG (default), PNG, or HTML. With format:"png" the chart comes back as an inline IMAGE you and the user can both see — render, look at the result, fix issues, re-render. Always returns structured frame metadata. When MCP_PUBLIC_URL is set the response includes stateless `urls` ({png,svg,bpc}). Set modelVisible:false to drop the inline image from the response entirely, spending no image tokens (reach the image via `urls.png` or `save`). Pass `save:<path>` to write the output into MCP_FS_WRITE_DIR instead of returning it inline. Width/height are capped at 1600; PNGs are rasterized at 2× for retina sharpness.list_chart_typesReference list of every chart type the renderer supports, with aliases and one-line summaries. To choose a type for a dataset, call recommend_chart_type instead.describe_chart_typeReturn everything an LLM needs to write a .bpc for a given chart type — typically your second call, after recommend_chart_type. Input: { chartType: "bar-horizontal" } (or any canonical/alias name). Returns summary, when-to-use, when-NOT-to-use, full property list with enum choices, data-shape example, and a pointer to a canonical sample.get_exampleReturn a canonical .bpc example. Pass { name } for a specific sample id, { chartType } for the first sample of that type, or no args for a starter sample.search_examplesFind canonical .bpc examples by topic keywords and/or chart type. Returns ranked pointers { id, title, description, chartType } — call get_example with an id to fetch the full DSL.list_palettesList every named colour palette with its label and hex colours, for use in `colorPalette = "<name>"`.get_grammarReturn the .bpc DSL grammar as markdown. Pass { section: "chart" | "data" | "properties" | "scenes" | "annotations" } for a focused subset, or no args for the full grammar.export_chartTurn a validated .bpc source into shareable URLs plus an inline visual preview of what was published. Returns { copyUrl, embedUrl, urls?, frame } and a PNG preview image block so you can confirm the chart looks right before sharing. copyUrl opens an editable copy in the editor; embedUrl is a read-only iframe target; urls.{png,svg,bpc} (when MCP_PUBLIC_URL is set) are stateless rendered-image/source links. Set modelVisible:false to drop the inline preview from the response entirely, spending no image tokens. Requires BLUEPRINT_CHART_EDITOR_URL; preview failures never block the export.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
MCP Server Chart
{
"mcpServers": {
"antv-mcp-server-chart": {
"command": "npx",
"args": [
"-y",
"@antv/mcp-server-chart"
]
}
}
}
Blueprint Chart
{
"mcpServers": {
"blueprint-chart": {
"command": "npx",
"args": [
"-y",
"@blueprint-chart/mcp"
]
}
}
}
Frequently asked questions
MCP Server Chart is categorized under Data Visualization and uses a local stdio subprocess. Blueprint Chart belongs to Data Visualization and uses a local stdio subprocess. Pick MCP Server Chart for data visualization work and Blueprint Chart for data visualization.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
MCP Server Chart is listed as free. Auth: no auth required. Blueprint Chart has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add antv-mcp-server-chart and blueprint-chart as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, MCP Server Chart has a quality signal of 71/100 (Great) with 9 views, 0 installs and 4,404 GitHub stars. Blueprint Chart has 59/100 (Good) with 1 views, 0 installs and 0 GitHub stars.