diff --git a/.tt_skip b/.tt_skip
index d03b8a1..5e9ef8d 100644
--- a/.tt_skip
+++ b/.tt_skip
@@ -1 +1,2 @@
-# add paths to tool repositories that should be ignored by CI
\ No newline at end of file
+# add paths to tool repositories that should be ignored by CI
+tools/visinity
\ No newline at end of file
diff --git a/tools/visinity/archive_generate.py b/tools/visinity/archive_generate.py
new file mode 100644
index 0000000..f74eb2a
--- /dev/null
+++ b/tools/visinity/archive_generate.py
@@ -0,0 +1,230 @@
+import csv
+import json
+import os
+import re
+import shutil
+import sys
+import time
+
+
+from zipfile import ZipFile, ZIP_BZIP2
+
+from minerva_analysis import app
+
+
+app.config['IS_DOCKER'] = False
+
+# create a non-serving test client to replace http request
+requests = app.test_client()
+
+args = sys.argv[1:]
+
+input_dict = {}
+with open(args[0], 'r') as f:
+    input_dict = json.load(f)
+
+out_file = args[1]
+
+name_list = []
+with open(input_dict['dataset_names'], 'r') as f:
+    _reader = csv.reader(f)
+    header = next(_reader)
+    assert header[0].lower() == 'names'
+    for row_list in _reader:
+        row = row_list[0]
+        if row in name_list:
+            raise ValueError(f'dataset name {row} is a duplicate!'
+                             ' please ensure names are unique')
+        s = re.sub('[^A-z0-9.~]+', '-', row)
+        if s != row:
+            row = s
+        name_list.append(row)
+
+channel_files = input_dict['channel_files']
+label_files = input_dict['label_files']
+
+assert len(name_list) == len(channel_files) == len(label_files)
+
+radius = input_dict['n_radius']
+celltype_csv = input_dict['celltype_csv']
+
+# ensure env
+data_path = f"{os.getcwd()}/minerva_analysis/data"
+config_path = f"{data_path}/config.json"
+
+if not os.path.isdir(data_path):
+    os.mkdir(data_path)
+
+if not os.path.isfile(config_path):
+    with open(config_path, 'w') as f:
+        f.write('{}')
+
+url = 'http://127.0.0.1:8000'
+
+with open(f'{data_path}/names.csv', 'w') as name_csv_file:
+    name_csv_file.write(
+        ','.join(name_list)
+    )
+
+shutil.copyfile(celltype_csv, 'celltype.csv')
+
+payload_data = {
+    "action": "Upload",
+    "celltype_file": open('celltype.csv', 'rb'),
+    "neighborhood_radius": int(radius),
+}
+
+for i, name in enumerate(name_list):
+    new_quant_csv = f'quant{i}.csv'
+    shutil.copyfile(input_dict['quant_csvs'][i], new_quant_csv)
+    _sub_d = {
+        f'name-{i+1}': name,
+        f'channel_file-{i+1}': channel_files[i],
+        f'label_file-{i+1}': label_files[i],
+        f'csv_file-{i+1}': open(new_quant_csv, 'rb'),
+    }
+    payload_data.update(_sub_d)
+
+
+# payload = {
+#   'data': {
+#     "action": "Upload",
+#     "name-1": dataset_name,
+#     "neighborhood_radius": int(n_radius),
+#     "channel_file-1": channel_file,
+#     "label_file-1": label_file,
+#     "csv_file-1": open(quant_target, 'rb'),
+#     "celltype_file": open(celltype_target, 'rb')
+#   }
+# }
+
+resp = requests.post(f"{url}/upload", data=payload_data)
+
+resp_regex = 'passVariablesToFrontend\((.*)\);'
+json_string = re.search(resp_regex, resp.text).group(1)
+combinedChannelData = json.loads(json_string)
+
+
+# def prep_header(_pre_sorted_headers: List[dict]):
+#     header_list = []
+#     # x_pos_terms = ['x_centroid', 'cellposition_x', 'x_position', 'x']
+#     # y_pos_terms = ['y_centroid', 'cellposition_y', 'y_position', 'y']
+#     # phenotype_terms = ['celltype', 'phenotype']
+
+#     _header_prefix = [None, None, None]
+#     _sorted_headers = []
+#     for header in _pre_sorted_headers[1:]:
+#         if header['fullName'].lower() in x_pos_terms:
+#             assert (_header_prefix[0] is None)
+#             _header_prefix[0] = header
+#         elif header['fullName'].lower() in y_pos_terms:
+#             assert (_header_prefix[1] is None)
+#             _header_prefix[1] = header
+#         elif header['fullName'].lower() in phenotype_terms:
+#             assert (_header_prefix[2] is None)
+#             _header_prefix[2] = header
+#         else:
+#             _sorted_headers.append(header)
+#     _i = 1
+#     all_headers = _header_prefix + _sorted_headers
+#     all_headers: dict
+#     for header in all_headers:
+#         header_list.extend(
+#             chunkify(header['fullName'], _i)
+#         )
+#     return header_list
+
+
+def chunkify(fullname, idx):
+    non_norm_markers = [
+        'majoraxislength', 'number_neighbors', 'minoraxislength', 'neighbor_1',
+        'solidity', 'eccentricity', 'y_position', 'x_position', 'neighbor_2',
+        'percent_touching', 'orientation', 'neighbor_4', 'extent', 'cellid',
+        'field_col', 'eulernumber', 'neighbor_3', 'neighbor_5', 'perimeter',
+        'field_row']
+
+    return [
+        {
+            "name": f"fullName{idx}",
+            "value": fullname
+        },
+        {
+            "name": f"name{idx}",
+            "value": fullname
+        },
+        {
+            "name": f"normalize{idx}",
+            "value": "off" if fullname.lower() in non_norm_markers else "on"
+        },
+    ]
+
+
+x_pos_terms = ['x_centroid', 'cellposition_x', 'x_position', 'x']
+y_pos_terms = ['y_centroid', 'cellposition_y', 'y_position', 'y']
+phenotype_terms = ['celltype', 'phenotype']
+
+# headers should all be the same, so using [0]
+pre_sorted_headers = combinedChannelData[0]["csvHeader"]
+
+# fix issue with filename "*_<digits>" being mistakenly assumed to be 
+# non-segmentation files; weirdly channel names dont seem to matter,
+# only if it has an underscore and number
+for channel in combinedChannelData:
+    channel["labelName"] = 'segmentation'
+
+idfield = chunkify(pre_sorted_headers[0]['fullName'], 0)
+
+header_prefix = [None, None, None]
+sorted_headers = []
+
+for header in pre_sorted_headers[1:]:
+    if header['fullName'].lower() in x_pos_terms:
+        assert (header_prefix[0] is None)
+        header_prefix[0] = header
+    elif header['fullName'].lower() in y_pos_terms:
+        assert (header_prefix[1] is None)
+        header_prefix[1] = header
+    elif header['fullName'].lower() in phenotype_terms:
+        assert (header_prefix[2] is None)
+        header_prefix[2] = header
+    else:
+        sorted_headers.append(header)
+
+
+all_headers = header_prefix + sorted_headers
+all_headers: dict
+
+headerlist = []
+i = 1
+for header in all_headers:
+    headerlist.extend(
+        chunkify(header['fullName'], i)
+    )
+    i += 1
+
+payload = {
+    'originalData': combinedChannelData,
+    'headerList': headerlist,
+    'normalizeCsv': False,
+    'idField': idfield
+}
+
+# execute request
+start = time.time()
+resp = requests.post(f"{url}/save_config", json=payload)
+duration = time.time() - start
+print(f"processing duration:\n\t{duration} sec ({duration/60} mins)")
+
+time.sleep(5)
+
+# extract relevant config.json bit
+with open(config_path, 'r') as innie:
+    config = json.load(innie)
+
+# zip it n ship it
+with ZipFile(f'{out_file}', 'w', ZIP_BZIP2) as zipped:
+    path_len = len(data_path) + 1
+    for base, dirs, files in os.walk(data_path):
+        for file in files:
+            file_name = os.path.join(base, file)
+            zipped.write(file_name, file_name[path_len:])
diff --git a/tools/visinity/archive_ingest.py b/tools/visinity/archive_ingest.py
new file mode 100644
index 0000000..4ac5817
--- /dev/null
+++ b/tools/visinity/archive_ingest.py
@@ -0,0 +1,48 @@
+import json
+import sys
+
+from os.path import isfile
+
+from zipfile import ZipFile
+
+
+with open(sys.argv[1], 'r') as f:
+    arg_dict = json.load(f)
+
+arch_zip = arg_dict['vis_archive']
+og_channels = arg_dict['channel_files']
+og_segs = arg_dict['label_files']
+
+
+data_path = '/visinity/minerva_analysis/data'
+conf_path = f'{data_path}/config.json'
+
+
+with ZipFile(arch_zip, 'r') as zippy:
+    zippy.extractall(f'{data_path}')
+
+with open(f'{data_path}/names.csv', 'r') as f:
+    name_list = f.read().split(',')
+
+with open(conf_path, 'r') as f:
+    config = json.load(f)
+
+
+def reconfigure(channel, seg, old_config):
+    subconfig = dict(old_config)
+    if not subconfig['segmentation'].startswith(data_path) or not isfile(subconfig['segmentation']):
+        subconfig['segmentation'] = seg
+    subconfig['channelFile'] = channel
+    return subconfig
+
+
+new_config = {}
+
+for i, name in enumerate(name_list):
+    name = name_list[i]
+    channel = og_channels[i]
+    seg = og_segs[i]
+    new_config[name] = reconfigure(channel, seg, config[name])
+
+with open(conf_path, 'w') as f:
+    f.write(json.dumps(new_config))
diff --git a/tools/visinity/dependencies/Dockerfile b/tools/visinity/dependencies/Dockerfile
new file mode 100644
index 0000000..749fed6
--- /dev/null
+++ b/tools/visinity/dependencies/Dockerfile
@@ -0,0 +1,49 @@
+FROM mambaorg/micromamba
+
+ARG TAG
+ARG PIP_NO_COMPILE="true"
+
+USER root
+
+RUN <<APT-INSTALL
+    set -e
+    apt-get update
+    apt-get install -y libgl1-mesa-glx curl unzip
+    rm -rf /var/lib/apt/lists/*
+APT-INSTALL
+
+RUN <<VISINITY
+    set -e
+    cd /tmp/
+    curl -L https://github.com/labsyspharm/visinity/archive/refs/tags/v$TAG.zip -o $TAG.zip
+    unzip $TAG.zip
+    rm -rf $TAG.zip
+    mv visinity-$TAG /visinity
+    useradd -ms /bin/bash visinity
+    echo -e '[global]\nno-cache-dir = True' >> /etc/pip.conf
+    chmod -R 0777 /visinity
+    chown -R visinity /visinity
+    micromamba install -n base -y -c conda-forge python=3.9 pip=24.0 openslide-python=1.3.1
+    micromamba install -n base -y -f /visinity/requirements.yml
+    micromamba clean --all --force-pkgs-dirs -y
+VISINITY
+
+RUN <<ENVMAKER
+    echo -e '#!/bin/bash\nmicromamba activate base\n$*' >> /bin/vis-env
+    chmod 755 /bin/vis-env
+ENVMAKER
+
+USER visinity
+
+SHELL [ "micromamba", "run", "-n", "base", "/bin/bash", "-c" ]
+
+RUN <<PIPPERY
+    set -e
+    pip install --no-dependencies lightkit pycave
+PIPPERY
+
+ENV BASH_ENV='/usr/local/bin/_activate_current_env.sh'
+
+EXPOSE 8000
+WORKDIR /visinity/
+CMD ["python", "run.py"]
\ No newline at end of file
diff --git a/tools/visinity/macros.xml b/tools/visinity/macros.xml
new file mode 100644
index 0000000..a12088f
--- /dev/null
+++ b/tools/visinity/macros.xml
@@ -0,0 +1,19 @@
+<?xml version="1.0"?>
+<macros>
+    <xml name="requirements">
+        <requirements>
+            <container type="docker">quay.io/goeckslab/visinity:1.17v0</container>
+        </requirements>
+    </xml>
+    <xml name="version_cmd">
+        <version_command>echo @TOOL_VERSION@</version_command>
+    </xml>
+    <xml name="citations">
+        <citations>
+            <citation type="doi">10.1109/TVCG.2022.3209378</citation>
+        </citations>
+    </xml>
+
+    <token name="@TOOL_VERSION@">1.17</token>
+    <token name="@VERSION_SUFFIX@">0</token>
+</macros>
\ No newline at end of file
diff --git a/tools/visinity/static/images/dataset_names_example.png b/tools/visinity/static/images/dataset_names_example.png
new file mode 100644
index 0000000..b403a13
Binary files /dev/null and b/tools/visinity/static/images/dataset_names_example.png differ
diff --git a/tools/visinity/static/images/phenotype_id_example.png b/tools/visinity/static/images/phenotype_id_example.png
new file mode 100644
index 0000000..ad179c8
Binary files /dev/null and b/tools/visinity/static/images/phenotype_id_example.png differ
diff --git a/tools/visinity/test-data/celltypes.csv b/tools/visinity/test-data/celltypes.csv
new file mode 100644
index 0000000..bdb9562
--- /dev/null
+++ b/tools/visinity/test-data/celltypes.csv
@@ -0,0 +1,5 @@
+phenotypeID,phenotype
+0,epithelial
+1,tcell
+2,bcell
+3,macrophage
diff --git a/tools/visinity/test-data/dataset_names.csv b/tools/visinity/test-data/dataset_names.csv
new file mode 100644
index 0000000..0409edb
--- /dev/null
+++ b/tools/visinity/test-data/dataset_names.csv
@@ -0,0 +1,2 @@
+names
+img_1
diff --git a/tools/visinity/test-data/test_image.ome.tiff b/tools/visinity/test-data/test_image.ome.tiff
new file mode 100644
index 0000000..e4a8fd5
Binary files /dev/null and b/tools/visinity/test-data/test_image.ome.tiff differ
diff --git a/tools/visinity/test-data/test_mask.tiff b/tools/visinity/test-data/test_mask.tiff
new file mode 100644
index 0000000..b834911
Binary files /dev/null and b/tools/visinity/test-data/test_mask.tiff differ
diff --git a/tools/visinity/test-data/test_quant.csv b/tools/visinity/test-data/test_quant.csv
new file mode 100644
index 0000000..d764d38
--- /dev/null
+++ b/tools/visinity/test-data/test_quant.csv
@@ -0,0 +1,41 @@
+CellID,CHAN_0,CHAN_1,X_centroid,Y_centroid,Area,MajorAxisLength,MinorAxisLength,Eccentricity,Solidity,Extent,Orientation,phenotype
+1,51.14091983548991,2.290488748001694,1275.204120950442,1094.3768565455614,146374,2281.259866065922,1725.3575809195545,0.6542043213246477,0.051162046,0.047094427,-0.168143532,0
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diff --git a/tools/visinity/vis-postprocess.xml b/tools/visinity/vis-postprocess.xml
new file mode 100644
index 0000000..a17765b
--- /dev/null
+++ b/tools/visinity/vis-postprocess.xml
@@ -0,0 +1,67 @@
+<tool id="visinity_postprocess" name="Visualize Visinity Archive" tool_type="interactive" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="22.01">
+    <description>Visualize pre-processed Visinity archives</description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <expand macro="version_cmd"/>
+    <entry_points>
+        <entry_point name="Visualize Visinity Archive" requires_domain="True">
+            <port>8000</port>
+            <url>/</url>
+        </entry_point>
+    </entry_points>
+    <command detect_errors="aggressive">
+        <![CDATA[
+    cp working/inputs.json /visinity/ &&
+    cp "$__tool_directory__/archive_ingest.py" /visinity/archive_ingest.py &&
+    cd /visinity/ &&
+    vis-env python archive_ingest.py inputs.json &&
+    vis-env python run.py;
+        ]]>
+    </command>
+    <configfiles>
+	    <inputs name='inputs' filename='inputs.json' data_style='paths'/>
+    </configfiles>
+    <inputs>
+        <param label='Visinity Archive' name='vis_archive' type='data' format='zip' help="Output of Create Visinity Archive tool"/>
+        <param label='Registered Images' name='channel_files' type='data_collection' collection_type='list' format='ome.tiff' help="Collection of properly formatted OME-TIFF images (Example: output of ASHLAR)"/>
+        <param label='Segmentation Masks' name='label_files' type='data_collection' collection_type='list' format='tiff' help="Collection of masks (tiff) as generated by cell/nuclear segmentation tool (Mesmer, S3segmenter, etc.)"/>
+    </inputs>
+    <outputs>
+        <data name="output" format="txt"/>
+    </outputs>
+    <tests>
+    </tests>
+    <help><![CDATA[
+**Visualize a Visinity Archive**
+
+Running Visinity in Galaxy requires execution of two separate tools in succession:
+
+1. Create Visinity Archive 
+2. Visualize Visinity Archive (**this tool**)
+
+**Archive visualizer inputs**
+
+1. **Visinity Archive**        Output of *Create Visinity Archive* (Tool 1)
+2. **Registered Images**       Same *Registered Images* collection used for Tool 1 (Collection of properly formatted OME-TIFF images (Example: output of ASHLAR))
+3. **Segmentation Masks**      Same *Segmentation Masks* collection used for Tool 1 (Collection of masks (tiff) as generated by cell/nuclear segmentation tool (Mesmer, S3segmenter, etc.))
+
+**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**
+
+**IMPORTANT NOTE**
+
+**Registered image and segmentation mask collections must be the same collections used for archive building!**
+
+**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**
+   
+**Outputs**
+
+This is an interactive tool. Once the tool is running (turns orange in the history panel), 
+view the Visinity dashboard by navigating to User > Active InteractiveTools
+
+Once the Visinity dashboard is launched, see the Visinity publication (https://doi.org/10.1109%2FTVCG.2022.3209378) for navigating Visinity and conducting analyses. 
+    ]]>
+    </help>
+    <expand macro="citations" />
+</tool>
diff --git a/tools/visinity/vis-preprocess.xml b/tools/visinity/vis-preprocess.xml
new file mode 100644
index 0000000..2e6e27e
--- /dev/null
+++ b/tools/visinity/vis-preprocess.xml
@@ -0,0 +1,122 @@
+<tool id="visinity_preprocess" name="Create Visinity Archive" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="22.01">
+    <description>Create an archive of pre-processed Visinity files</description>
+    <macros>
+        <import>macros.xml</import>
+    </macros>
+    <expand macro="requirements"/>
+    <expand macro="version_cmd"/>
+    <command detect_errors="aggressive">
+        <![CDATA[
+    cp inputs.json /visinity/ &&
+    cd /visinity/ &&
+    cp "$__tool_directory__/archive_generate.py" "./archive_generate.py" &&
+    vis-env python archive_generate.py inputs.json '$out_archive';
+        ]]>
+    </command>
+    <configfiles>
+	    <inputs name='inputs' filename='inputs.json' data_style='paths'/>
+    </configfiles>
+    <inputs>
+        <param label='Image IDs/Names CSV' name='dataset_names' type='data' format='csv' help="Single column CSV file with IDs for each image in the cohort under column titled 'names'"/>
+        <param label='Registered Images' name='channel_files' type='data_collection' collection_type='list' format='ome.tiff' help="Collection of properly formatted OME-TIFF images (Example: output of ASHLAR)"/>
+        <param label='Segmentation Masks' name='label_files' type='data_collection' collection_type='list' format='tiff' help="Collection of masks (tiff) as generated by cell/nuclear segmentation tool (Mesmer, S3segmenter, etc.)"/>
+        <param label='Quantification Files' name='quant_csvs' type='data_collection' collection_type='list' format='csv' help="Collection of feature quantification files (CSV) as generated by the MCMICRO Quantification module (MCQUANT)"/>
+        <param label='Neighborhood Radius' name='n_radius' type='integer' value='20' min='1' max='1000' help="Radius to define a cell's local neighborhood for pattern detection in microns > 0"/>
+        <param label='Cell Type CSV' name='celltype_csv' type='data' format='csv' help="File mapping cell-type indices to cell-type names. Expected column names are phenotypeID, phenotype"/>
+    </inputs>
+    <outputs>
+        <data name="out_archive" format="zip"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="dataset_names" value="dataset_names.csv" />
+            <param name="channel_files">
+                <collection type="list">
+                    <element name="i1" value="test_image.ome.tiff" />
+                </collection>
+            </param>
+            <param name="label_files">
+                <collection type="list">
+                    <element name="m1" value="test_mask.tiff" />
+                </collection>
+            </param>
+            <param name="quant_csvs">
+                <collection type="list">
+                    <element name="q1" value="test_quant.csv" />
+                </collection>
+            </param>
+            <param name="celltype_csv" value="celltypes.csv" />
+            <output name="out_archive">
+                <assert_contents>
+                    <has_size value="680000" delta="10000" />
+                </assert_contents>
+            </output>
+            <!-- FIXME: replace with chunk below once CI is upgraded to Galaxy v24 -->
+            <!-- <output name="out_archive">
+                <has_archive_member path="./config.json"/>
+                <has_archive_member path="./test_image/embedding.npy"/>
+                <has_archive_member path="./test_image/neighborhood.npy"/>
+            </output> -->
+        </test>
+    </tests>
+    <help><![CDATA[
+**Create a Visinity Archive**
+
+Running Visinity in Galaxy requires execution of two separate tools in succession:
+
+1. Create Visinity Archive (**this tool**)
+2. Visualize Visinity Archive 
+
+Creating a Visinity archive takes a cohort of multiplex tissue images and associated data 
+(masks, feature quantification, and cell types) and performs all of the necessary preprocessing to 
+create an interactive Visinity dashboard (executed in tool 2).
+
+**Archive builder inputs**
+
+1. **Image IDs/Names CSV**        Single column CSV file with IDs for each image in the cohort under column titled 'names'
+
+Example:
+
+.. image:: dataset_names_example.png
+
+2. **Registered Images**       Collection of properly formatted OME-TIFF images (Example: output of ASHLAR)
+3. **Segmentation Masks**      Collection of masks (tiff) as generated by cell/nuclear segmentation tool (Mesmer, S3segmenter, etc.)
+4. **Quantification Files**    Collection of feature quantification files (CSV) as generated by the MCMICRO Quantification module (MCQUANT)
+
+Expected columns for Quantification Files: `CellID, Marker_0, ... Marker_n, X_centroid, Y_centroid`
+
+5. **Neighborhood Radius**     Radius to define a cell's local neighborhood for pattern detection in microns > 0
+6. **Cell Type CSV**           File mapping cell-type indices to cell-type names. Expected column names are phenotypeID, phenotype
+
+Example:  
+
+.. image:: phenotype_id_example.png
+
+**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**  
+
+**IMPORTANT NOTE**
+
+**The order of all input collections and dataset names matters!**
+**For instance, the first mask in the segmentation collection should have been derived**
+**from the first image in the registered image collection, and should be match the first name**
+**in the datasets name file, etc.**
+
+**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**  
+   
+**Outputs**
+
+The output of the archive builder is a single dataset in Galaxy that is used as the primary input for the 
+visualization tool (2)
+
+**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**
+
+**IMPORTANT NOTE**
+
+**Do not delete any of the input collections, as they are also required inputs for the visualization tool**
+
+**~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~**
+
+]]>
+    </help>
+    <expand macro="citations" />
+</tool>