Blueprint Chart vs Dgmo MCP
A side-by-side look at the Blueprint Chart and Dgmo MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Blueprint Chart for data visualization work as a local process; choose Dgmo MCP 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 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.
Choose Dgmo MCP when
- You need dedicated capabilities in the Data Visualization domain.
- You prefer a local stdio subprocess transport.
- You want tools like
render_diagram, validate_diagram, suggest_chart_type.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Data Visualization | Data Visualization |
| Quality signal | 59/100 · Good | 57/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 0 | 3 |
| Directory activity | 1 views 0 installs 0 upvotes | 2 views 0 installs 0 upvotes |
| Tools | 11 | 14 |
| Full listing | View Blueprint Chart | View Dgmo MCP |
Tools & capabilities
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.
Dgmo MCP tools 14
render_diagramRender DGMO markup to **SVG or PNGvalidate_diagramCheck markup and report parse errors, without renderingsuggest_chart_typeSuggest the chart types that fit a descriptionlist_chart_typesList all supported chart types, marking the beta onesget_language_referenceGet DGMO syntax documentation for accurate generationget_examplesFetch worked examples for a chart typeshare_diagramGet a shareable **diagrammo.app** URL — hand your diagram to the web editoropen_in_appOpen the diagram **straight into the Diagrammo desktop app** for editingcheck_app_installedReport whether the desktop app is installedpreview_diagramRender one or more diagrams and open an **HTML preview** in the browsergenerate_reportBuild a polished **multi-section HTML report** with ToC and optional sourceput_space_diagramWrite a diagram into a **Diagrammo Cloud space**, by folder and title- +2 more on the listing page
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.
Blueprint Chart
{
"mcpServers": {
"blueprint-chart": {
"command": "npx",
"args": [
"-y",
"@blueprint-chart/mcp"
]
}
}
}
Dgmo MCP
{
"mcpServers": {
"dgmo-mcp": {
"command": "npx",
"args": [
"-y",
"@diagrammo/dgmo-cli"
]
}
}
}
Frequently asked questions
Blueprint Chart is categorized under Data Visualization and uses a local stdio subprocess. Dgmo MCP belongs to Data Visualization and uses a local stdio subprocess. Pick Blueprint Chart for data visualization work and Dgmo MCP 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.
Blueprint Chart has no declared pricing — check the project's own site. Dgmo MCP 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 blueprint-chart and dgmo-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Blueprint Chart has a quality signal of 59/100 (Good) with 1 views, 0 installs and 0 GitHub stars. Dgmo MCP has 57/100 (Good) with 2 views, 0 installs and 3 GitHub stars.