Meansplot with Tukey HSD confidence intervals in R-CodePudding

I'm trying to make a meansplot with confidence intervals, but I would like the intervals to be Tukey HSD intervals after an ANOVA is computed.

I'll use the next example here to explain, in the dataframe there is a factor: poison {1,2,3}

library(magrittr) 
library(ggplot2)
library(ggpubr)
library(dplyr) 
library("agricolae") 
PATH <- "https://raw.githubusercontent.com/guru99-edu/R-Programming/master/poisons.csv"
df <- read.csv(PATH) %>%
    select(-X) %>%
    mutate(poison = factor(poison, ordered = TRUE))
glimpse(df)


ggplot(df, aes(x = poison, y = time, fill = poison))  
    geom_boxplot()  
    geom_jitter(shape = 15,
        color = "steelblue",
        position = position_jitter(0.21))  
        theme_classic()

anova_one_way <- aov(time ~ poison, data = df)
summary(anova_one_way)

# Use TukeyHSD
tukeyHSD <- TukeyHSD(anova_one_way)
plot(tukeyHSD)

I would like the plot to be similar to the one from statgraphics, where you can see the mean point and the lenght of the bars is the HSD tuckey intervals, so in one simple glimpse you can apreciate the best level and if it is better and is statistically significantly better.

Statgraphics meansplot

I have seen some examples in more complex questions but is for boxplots and I dont understand it enough to adapt the solutions here.

Here we can see that there are significant differences between 1 and 3, and between 2 and 3, but that the difference between 1 and 2 is non-significant.