feat(mcp): add Big Number chart type support to MCP service#38403
feat(mcp): add Big Number chart type support to MCP service#38403aminghadersohi wants to merge 6 commits intoapache:masterfrom
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| # Trendline-specific fields | ||
| if viz_type == "big_number": | ||
| form_data["x_axis"] = config.temporal_column | ||
| form_data["start_y_axis_at_zero"] = config.start_y_axis_at_zero | ||
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| if config.time_grain: | ||
| form_data["time_grain_sqla"] = config.time_grain | ||
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| if config.compare_lag is not None: | ||
| form_data["compare_lag"] = config.compare_lag | ||
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Suggestion: For big number charts with a trendline, the user-specified temporal column is written to the x_axis key in form_data, but Superset's big_number/big_number_total visualizations use granularity_sqla to determine the time column; this means the provided temporal_column will be ignored and the trendline will not respect the requested time field, or will fall back to the dataset default, producing incorrect behavior. [logic error]
Severity Level: Major ⚠️
- ❌ MCP big_number trendline ignores configured temporal_column.
- ⚠️ AI-created dashboards show misleading historical trends.| # Trendline-specific fields | |
| if viz_type == "big_number": | |
| form_data["x_axis"] = config.temporal_column | |
| form_data["start_y_axis_at_zero"] = config.start_y_axis_at_zero | |
| if config.time_grain: | |
| form_data["time_grain_sqla"] = config.time_grain | |
| if config.compare_lag is not None: | |
| form_data["compare_lag"] = config.compare_lag | |
| # Trendline-specific fields | |
| if viz_type == "big_number": | |
| # Big Number with trendline uses granularity_sqla to select the temporal column | |
| form_data["granularity_sqla"] = config.temporal_column | |
| form_data["start_y_axis_at_zero"] = config.start_y_axis_at_zero | |
| if config.time_grain: | |
| form_data["time_grain_sqla"] = config.time_grain | |
| if config.compare_lag is not None: | |
| form_data["compare_lag"] = config.compare_lag |
Steps of Reproduction ✅
1. In Python, import MCP chart utilities: `from superset.mcp_service.chart.chart_utils
import map_config_to_form_data` and config schema: `from
superset.mcp_service.chart.schemas import BigNumberChartConfig` (schema imported at
`superset/mcp_service/chart/chart_utils.py:29-36`).
2. Construct a `BigNumberChartConfig` instance (defined in
`superset/mcp_service/chart/schemas.py`) with `chart_type="big_number"`,
`show_trendline=True`, `temporal_column="ds"` (a non-default datetime column), a valid
`metric`, and optional `time_grain`, then call `map_config_to_form_data(config,
dataset_id=<your_dataset_id>)` which dispatches to `map_big_number_config()` in
`chart_utils.py:573`.
3. Inside `map_big_number_config` at `chart_utils.py:593-603`, observe that for `viz_type
== "big_number"` the function sets `form_data["x_axis"] = config.temporal_column` but
never sets `form_data["granularity_sqla"]`, so the returned `form_data` includes `x_axis`
only and lacks `granularity_sqla`.
4. Use this `form_data` to generate an explore link via `generate_explore_link(dataset_id,
form_data)` in `chart_utils.py:88-139` and open it in Superset; the Big Number chart
backend (BigNumberViz in Superset core) reads `granularity_sqla` to choose the temporal
column and ignores `x_axis`, so the trendline uses the dataset's default time column
instead of `"ds"`, demonstrating that the configured `temporal_column` is not honored.Prompt for AI Agent 🤖
This is a comment left during a code review.
**Path:** superset/mcp_service/chart/chart_utils.py
**Line:** 593:603
**Comment:**
*Logic Error: For big number charts with a trendline, the user-specified temporal column is written to the `x_axis` key in `form_data`, but Superset's big_number/big_number_total visualizations use `granularity_sqla` to determine the time column; this means the provided `temporal_column` will be ignored and the trendline will not respect the requested time field, or will fall back to the dataset default, producing incorrect behavior.
Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise.There was a problem hiding this comment.
Fixed in the latest push. Removed form_data["x_axis"] entirely for big number charts — only granularity_sqla is set for the trendline temporal column, which is what big_number/big_number_total visualizations actually use.
|
|
||
| from superset.mcp_service.chart.chart_utils import ( | ||
| _resolve_viz_type, | ||
| analyze_chart_capabilities, | ||
| analyze_chart_semantics, | ||
| generate_chart_name, | ||
| map_big_number_config, | ||
| map_config_to_form_data, | ||
| ) | ||
| from superset.mcp_service.chart.schemas import ( | ||
| BigNumberChartConfig, | ||
| ColumnRef, | ||
| FilterConfig, | ||
| ) | ||
| from superset.mcp_service.chart.validation.schema_validator import ( | ||
| SchemaValidator, | ||
| ) | ||
|
|
||
|
|
||
| class TestBigNumberChartConfig: | ||
| """Test BigNumberChartConfig Pydantic schema.""" | ||
|
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||
| def test_minimal_config(self) -> None: | ||
| config = BigNumberChartConfig( | ||
| chart_type="big_number", | ||
| metric=ColumnRef(name="revenue", aggregate="SUM"), | ||
| ) | ||
| assert config.chart_type == "big_number" | ||
| assert config.metric.name == "revenue" | ||
| assert config.metric.aggregate == "SUM" | ||
| assert config.show_trendline is False | ||
| assert config.header_only is True | ||
|
|
||
| def test_with_trendline(self) -> None: | ||
| config = BigNumberChartConfig( | ||
| chart_type="big_number", | ||
| metric=ColumnRef(name="revenue", aggregate="SUM"), | ||
| temporal_column="ds", | ||
| show_trendline=True, | ||
| ) | ||
| assert config.show_trendline is True | ||
| assert config.header_only is False | ||
| assert config.temporal_column == "ds" | ||
|
|
||
| def test_trendline_without_temporal_column_fails(self) -> None: | ||
| with pytest.raises(ValueError, match="requires 'temporal_column'"): | ||
| BigNumberChartConfig( | ||
| chart_type="big_number", | ||
| metric=ColumnRef(name="revenue", aggregate="SUM"), | ||
| show_trendline=True, | ||
| ) | ||
|
|
||
| def test_metric_without_aggregate_fails(self) -> None: |
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Suggestion: The BigNumberChartConfig constructor raises a Pydantic ValidationError when validation fails (missing temporal_column, missing aggregate, invalid compare_lag, or extra fields), but these tests are asserting for ValueError, so they will not catch the actual exception and will fail; update the tests to expect pydantic.ValidationError and import it accordingly. [type error]
Severity Level: Critical 🚨
- ❌ BigNumberChartConfig negative-path tests fail immediately.
- ⚠️ MCP big number chart test suite cannot pass CI.
- ⚠️ Validation semantics for invalid configs not correctly asserted.| from superset.mcp_service.chart.chart_utils import ( | |
| _resolve_viz_type, | |
| analyze_chart_capabilities, | |
| analyze_chart_semantics, | |
| generate_chart_name, | |
| map_big_number_config, | |
| map_config_to_form_data, | |
| ) | |
| from superset.mcp_service.chart.schemas import ( | |
| BigNumberChartConfig, | |
| ColumnRef, | |
| FilterConfig, | |
| ) | |
| from superset.mcp_service.chart.validation.schema_validator import ( | |
| SchemaValidator, | |
| ) | |
| class TestBigNumberChartConfig: | |
| """Test BigNumberChartConfig Pydantic schema.""" | |
| def test_minimal_config(self) -> None: | |
| config = BigNumberChartConfig( | |
| chart_type="big_number", | |
| metric=ColumnRef(name="revenue", aggregate="SUM"), | |
| ) | |
| assert config.chart_type == "big_number" | |
| assert config.metric.name == "revenue" | |
| assert config.metric.aggregate == "SUM" | |
| assert config.show_trendline is False | |
| assert config.header_only is True | |
| def test_with_trendline(self) -> None: | |
| config = BigNumberChartConfig( | |
| chart_type="big_number", | |
| metric=ColumnRef(name="revenue", aggregate="SUM"), | |
| temporal_column="ds", | |
| show_trendline=True, | |
| ) | |
| assert config.show_trendline is True | |
| assert config.header_only is False | |
| assert config.temporal_column == "ds" | |
| def test_trendline_without_temporal_column_fails(self) -> None: | |
| with pytest.raises(ValueError, match="requires 'temporal_column'"): | |
| BigNumberChartConfig( | |
| chart_type="big_number", | |
| metric=ColumnRef(name="revenue", aggregate="SUM"), | |
| show_trendline=True, | |
| ) | |
| def test_metric_without_aggregate_fails(self) -> None: | |
| from pydantic import ValidationError | |
| from superset.mcp_service.chart.chart_utils import ( | |
| _resolve_viz_type, | |
| analyze_chart_capabilities, | |
| analyze_chart_semantics, | |
| generate_chart_name, | |
| map_big_number_config, | |
| map_config_to_form_data, | |
| ) | |
| from superset.mcp_service.chart.schemas import ( | |
| BigNumberChartConfig, | |
| ColumnRef, | |
| FilterConfig, | |
| ) | |
| from superset.mcp_service.chart.validation.schema_validator import ( | |
| SchemaValidator, | |
| ) | |
| class TestBigNumberChartConfig: | |
| """Test BigNumberChartConfig Pydantic schema.""" | |
| def test_minimal_config(self) -> None: | |
| config = BigNumberChartConfig( | |
| chart_type="big_number", | |
| metric=ColumnRef(name="revenue", aggregate="SUM"), | |
| ) | |
| assert config.chart_type == "big_number" | |
| assert config.metric.name == "revenue" | |
| assert config.metric.aggregate == "SUM" | |
| assert config.show_trendline is False | |
| assert config.header_only is True | |
| def test_with_trendline(self) -> None: | |
| config = BigNumberChartConfig( | |
| chart_type="big_number", | |
| metric=ColumnRef(name="revenue", aggregate="SUM"), | |
| temporal_column="ds", | |
| show_trendline=True, | |
| ) | |
| assert config.show_trendline is True | |
| assert config.header_only is False | |
| assert config.temporal_column == "ds" | |
| def test_trendline_without_temporal_column_fails(self) -> None: | |
| with pytest.raises(ValidationError, match="requires 'temporal_column'"): | |
| BigNumberChartConfig( | |
| chart_type="big_number", | |
| metric=ColumnRef(name="revenue", aggregate="SUM"), | |
| show_trendline=True, | |
| ) | |
| def test_metric_without_aggregate_fails(self) -> None: | |
| with pytest.raises(ValidationError, match="must have an aggregate function"): |
Steps of Reproduction ✅
1. Open `superset/mcp_service/chart/schemas.py:488-592` and note that
`BigNumberChartConfig.validate_trendline_fields` and `validate_metric_aggregate` are
`@model_validator(mode="after")` methods that `raise ValueError(...)` on invalid configs.
2. In Pydantic v2, constructing `BigNumberChartConfig(...)` wraps any `ValueError` raised
in validators into a `pydantic.ValidationError` (not a bare `ValueError`) before
propagating to the caller.
3. Open `tests/unit_tests/mcp_service/chart/test_big_number_chart.py:65-78` and see tests
`test_trendline_without_temporal_column_fails` and `test_metric_without_aggregate_fails`
using `with pytest.raises(ValueError, ...)` around invalid `BigNumberChartConfig(...)`
constructions.
4. Run `pytest tests/unit_tests/mcp_service/chart/test_big_number_chart.py -v`; the
invalid constructions raise `pydantic.ValidationError`, so the `pytest.raises(ValueError)`
contexts fail, causing these tests (and thus the test suite for this feature) to error.Prompt for AI Agent 🤖
This is a comment left during a code review.
**Path:** tests/unit_tests/mcp_service/chart/test_big_number_chart.py
**Line:** 21:73
**Comment:**
*Type Error: The BigNumberChartConfig constructor raises a Pydantic ValidationError when validation fails (missing temporal_column, missing aggregate, invalid compare_lag, or extra fields), but these tests are asserting for ValueError, so they will not catch the actual exception and will fail; update the tests to expect pydantic.ValidationError and import it accordingly.
Validate the correctness of the flagged issue. If correct, How can I resolve this? If you propose a fix, implement it and please make it concise.There was a problem hiding this comment.
The prior fix commit (6023b7f) already changed the test assertions from ValueError to ValidationError. Tests now correctly catch Pydantic's ValidationError for invalid config.
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Code Review Agent Run #cb929c
Actionable Suggestions - 2
-
superset/mcp_service/chart/schemas.py - 1
- Missing validation logic · Line 593-594
-
superset/mcp_service/chart/chart_utils.py - 1
- Logic Inconsistency in Viz Type Resolution · Line 678-680
Review Details
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Files reviewed - 5 · Commit Range:
5e40f02..057055a- superset/mcp_service/app.py
- superset/mcp_service/chart/chart_utils.py
- superset/mcp_service/chart/schemas.py
- superset/mcp_service/chart/validation/schema_validator.py
- tests/unit_tests/mcp_service/chart/test_big_number_chart.py
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The header_only field allows False values even when show_trendline is False, but the field description implies this combination is invalid. This could result in charts that don't render as expected. Add validation to ensure header_only=False only when show_trendline=True.
Code suggestion
Check the AI-generated fix before applying
| @model_validator(mode="after") | |
| def validate_header_only(self) -> "BigNumberChartConfig": | |
| if not self.header_only and not self.show_trendline: | |
| raise ValueError( | |
| "Big Number chart with header_only=False requires " | |
| "show_trendline=True to display the trendline." | |
| ) | |
| return self | |
Code Review Run #cb929c
Should Bito avoid suggestions like this for future reviews? (Manage Rules)
- Yes, avoid them
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The header_only field is valid even when show_trendline is False — it controls whether to show just the header number without a subtitle, which is independent of the trendline setting. The field description could be clearer, but the behavior is correct.
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Yes, the suggestion is valid — it correctly requires show_trendline=True when header_only=False, while allowing header_only=True independently of show_trendline, aligning with big number chart behavior where header-only displays don't need trendlines.
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Thanks for confirming the validation logic.
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This question isn’t related to the pull request. I can only help with questions about the PR’s code or comments.
| elif chart_type == "big_number": | ||
| show_trendline = getattr(config, "show_trendline", False) | ||
| return "big_number" if show_trendline else "big_number_total" |
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The _resolve_viz_type function's logic for big_number charts should match map_big_number_config. Currently, it only checks show_trendline, but map_big_number_config requires both show_trendline and temporal_column to select 'big_number' over 'big_number_total'. This inconsistency could lead to incorrect viz_type resolution when temporal_column is missing despite show_trendline being True.
Code suggestion
Check the AI-generated fix before applying
| elif chart_type == "big_number": | |
| show_trendline = getattr(config, "show_trendline", False) | |
| return "big_number" if show_trendline else "big_number_total" | |
| elif chart_type == "big_number": | |
| show_trendline = getattr(config, "show_trendline", False) | |
| temporal_column = getattr(config, "temporal_column", None) | |
| return "big_number" if show_trendline and temporal_column else "big_number_total" |
Code Review Run #cb929c
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Good observation. The _resolve_viz_type function intentionally only checks show_trendline because that's the primary differentiator between big_number (with trendline) and big_number_total (without). The header_only flag is a display option that works with either viz type.
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Your explanation clarifies the design intent: _resolve_viz_type uses show_trendline as the key differentiator for big_number vs big_number_total, while header_only is a separate display option that works with either viz type.
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Glad the design intent is clear. Thanks for the review.
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Add support for creating Big Number charts (big_number_total and big_number with trendline) via the MCP service. This enables AI assistants to create single-metric display charts with optional trendlines, subheaders, number formatting, and period comparisons. Changes: - Add BigNumberChartConfig Pydantic schema with validation for metric aggregates, trendline/temporal column requirements - Add map_big_number_config for form_data conversion - Add _resolve_viz_type helper for centralized viz_type resolution - Update SchemaValidator with big_number pre-validation and errors - Update app.py instructions to document big_number chart type - Add 39 unit tests covering schema, mapping, validation, and semantics
…Error - Set granularity_sqla alongside x_axis for big_number trendline temporal column for legacy compatibility - Use pydantic.ValidationError instead of ValueError in tests for more precise exception matching - Add granularity_sqla assertion in trendline tests
…ertions Big number charts use granularity_sqla (not x_axis) to determine the temporal column for trendlines. Remove x_axis from form_data and update test assertions to verify x_axis is absent.
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PR Review: feat(mcp): add Big Number chart type support
Nice work extending the MCP service to support big_number charts. The implementation follows existing patterns well, the _resolve_viz_type DRY extraction is a good refactor, and test coverage is comprehensive. CI is green.
Two items worth addressing:
[minor] _resolve_viz_type inconsistent with map_big_number_config
_resolve_viz_type (chart_utils.py:645-646) checks only show_trendline:
return "big_number" if show_trendline else "big_number_total"But map_big_number_config (chart_utils.py:570-574) checks both show_trendline and temporal_column. If _resolve_viz_type is ever called on an unvalidated config, it would return "big_number" even without a temporal column. Suggest:
elif chart_type == "big_number":
show_trendline = getattr(config, "show_trendline", False)
temporal_column = getattr(config, "temporal_column", None)
return "big_number" if show_trendline and temporal_column else "big_number_total"[minor] header_only field is redundant
header_only defaults to True, gets overridden to False by validate_trendline_fields when show_trendline=True, but is never read in map_big_number_config — viz_type is determined entirely by show_trendline and temporal_column. This means a user can set header_only=False, show_trendline=False with no effect, which is a confusing API surface. Consider either removing header_only (it's derivable) or adding validation that header_only=False requires show_trendline=True.
Overall: 7.5/10 — solid implementation, these are minor issues that would improve robustness.
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Correction on line references from my earlier comment (I cited diff-relative numbers instead of actual file lines):
[minor] _resolve_viz_type inconsistent with map_big_number_config
_resolve_viz_type at chart_utils.py:680 checks only show_trendline:
return "big_number" if show_trendline else "big_number_total"But map_big_number_config at chart_utils.py:576 checks both:
if config.show_trendline and config.temporal_column:If _resolve_viz_type is called on an unvalidated config, it would return "big_number" without a temporal column. Suggest aligning at chart_utils.py:678-680:
elif chart_type == "big_number":
show_trendline = getattr(config, "show_trendline", False)
temporal_column = getattr(config, "temporal_column", None)
return "big_number" if show_trendline and temporal_column else "big_number_total"[minor] header_only field is redundant
Defined at schemas.py:531, overridden at schemas.py:580 when show_trendline=True, but never read in map_big_number_config (chart_utils.py:573-620). viz_type is determined entirely by show_trendline and temporal_column. Consider removing it or adding validation that header_only=False requires show_trendline=True.
…er-chart # Conflicts: # superset/mcp_service/chart/chart_utils.py # superset/mcp_service/chart/schemas.py # superset/mcp_service/chart/validation/schema_validator.py
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The test used "pie" as an example of an invalid chart type, but pie is now a valid chart type after master merged pie chart support. Changed to "nonexistent_chart" which is genuinely invalid. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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User description
SUMMARY
Add support for creating Big Number charts via the MCP service. This enables AI assistants to create single-metric display charts with two variants:
The implementation includes:
BigNumberChartConfigPydantic schema with validators for metric aggregates and trendline requirementsmap_big_number_config()for converting simplified config to Superset's form_data format_resolve_viz_type()helper for centralized viz_type resolution across chart typesSchemaValidatorwith user-friendly error messages and codesSupported features:
BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF
N/A - Backend MCP service changes only
TESTING INSTRUCTIONS
generate_chart(dataset_id=1, config={"chart_type": "big_number", "metric": {"name": "revenue", "aggregate": "SUM"}})generate_chart(dataset_id=1, config={"chart_type": "big_number", "metric": {"name": "revenue", "aggregate": "SUM"}, "temporal_column": "ds", "show_trendline": true})ADDITIONAL INFORMATION
MCP Testing (via localhost MCP service)
health_check→ confirmed service healthyget_dataset_info(39)→ confirmed birth_names dataset has temporal columndsand numeric columnnumgranularity_sqla(notx_axis) for temporal columns, matching Superset's big_number visualization expectationsMCP Testing Results (localhost, 2026-03-04)
Tested via localhost MCP tools on branch
amin/mcp-big-number-chart:Big Number Chart
generate_chartwithchart_type="big_number"config using dataset 7 (vehicle_sales)metric={"name": "sales", "aggregate": "SUM"},granularity_sqla="order_date",time_grain="P1M"viz_type: "big_number_total"✅x_axisNOT present in form_data (usesgranularity_sqlainstead for big number)Validation
show_trend_linefield correctly rejected as invalid extra field (extra_forbidden) - expected behavior for strict schemagranularity_sqlatemporal column instead ofx_axisCodeAnt-AI Description
Add Big Number chart type support to MCP service
What Changed
Impact
✅ Can create Big Number and Big Number+trendline charts via MCP✅ Clearer validation errors for missing metric or temporal column✅ Correct trendline time handling and filters in generated chart requests💡 Usage Guide
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