MCP Server Part 6: Format callback results for LLM consumption

[KoolADE85]

Summary

• Add formatters that enrich callback responses with LLM-friendly content (images, markdown tables) for certain data types
• PlotlyFigureResult — renders Graph.figure outputs as PNG images via kaleido, returned as ImageContent
• DataFrameResult — renders DataTable.data and AgGrid.rowData outputs as markdown tables, returned as TextContent

Manual verification:

importplotly.expressaspxfromdashimportDash, html, dcc, Input, Output, dash_tabledf=px.data.gapminder().query("year == 2007 and continent == 'Europe'")
app=Dash(__name__)
app.layout=html.Div([
dcc.Dropdown(id="metric", options=["gdpPercap", "lifeExp", "pop"], value="gdpPercap"),
dcc.Graph(id="chart"),
dash_table.DataTable(id="table"),
])
@app.callback(Output("chart", "figure"), Input("metric", "value"))defupdate_chart(metric):
"""Bar chart of the selected metric across European countries."""returnpx.bar(df, x="country", y=metric, title=f"{metric} in Europe (2007)")
@app.callback(Output("table", "data"), Input("metric", "value"))defupdate_table(metric):
"""Top 5 countries for the selected metric."""returndf.nlargest(5, metric)[["country", metric]].to_dict("records")
withapp.server.app_context():
fromdash.mcp.primitives.tools.callback_adapter_collectionimportCallbackAdapterCollectionfromdash.mcp.primitives.tools.callback_utilsimportrun_callbackfromdash.mcp.primitives.tools.resultsimportformat_callback_responsecollection=CallbackAdapterCollection(app)
foradapterincollection:
response=run_callback(adapter, {"metric": "lifeExp"})
result=format_callback_response(response, adapter)
foriteminresult.content:
ifitem.type=="text":
print(f"[text] {item.text[:200]}...")
elifitem.type=="image":
print(f"[image] {item.mimeType}, {len(item.data)} chars base64")
# update_chart: [text] JSON + [image] PNG# update_table: [text] JSON + [text] markdown table

[github-actions]

Thank you for your contribution to Dash! 🎉

This PR is exempt from requiring a linked issue due to its labels.

[camdecoster]

Looks good. I add a few minor suggestions.

[camdecoster]

Would using a dict instead of a list make more sense here? Then you wouldn't have to iterate through the list down below (assuming you could figure out which formatter to use before calling it).

[KoolADE85]

Thinking about this further, I'd like to keep the current structure for two reasons:

1. consistency: the pattern of "iterate providers, each decides if it applies" is already used for input schemas, tool descriptions, and resource providers; I think it's valuable to keep a consistent pattern here too.
2. flexibility: iterating lets each formatter decide dynamically whether it applies. While it's fairly static today, we are leaving room for multiple formatters to enrich the same output without restructuring later.

[camdecoster]

Why is this change necessary?

[KoolADE85]

just a style choice: I wanted it to read more clearly when it's subsequently used in the result formatter, that we are actually concerned with formatting Plotly figures, not more "generic" figures.