diff --git a/.gitignore b/.gitignore
index 07d8fa2d72..8d6beb6065 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,7 +1,9 @@
 /bazel-*
 /.idea
+.venv/
 .DS_Store
 *.pyc
 *.egg-info/
 *.swp
 node_modules
+uv.lock
diff --git a/DEVELOPMENT.md b/DEVELOPMENT.md
index b3a902e37e..942b94b92e 100644
--- a/DEVELOPMENT.md
+++ b/DEVELOPMENT.md
@@ -23,6 +23,17 @@ $ source tf/bin/activate
 (tf)$ pip uninstall -y tb-nightly
 ```
 
+If you prefer [uv](https://github.com/astral-sh/uv), you can manage the same
+development environment from the repository root with:
+
+```sh
+$ uv sync --extra tensorflow
+$ uv run bazel run //tensorboard -- --logdir /path/to/logs
+```
+
+This gives `uv` enough project metadata to manage dependencies from the repo
+root, while still using Bazel for the actual TensorBoard build.
+
 TensorBoard builds are done with [Bazel](https://bazel.build), so you may need to [install Bazel](https://docs.bazel.build/versions/master/install.html). The Bazel build will automatically "vulcanize" all the HTML files and generate a "binary" launcher script. When HTML is vulcanized, it means all the script tags and HTML imports are inlined into one big HTML file. Then the Bazel build puts that index.html file inside a static assets zip. The python HTTP server then reads static assets from that zip while serving.
 
 You can build and run TensorBoard via Bazel (from within the TensorFlow nightly virtualenv) as follows:
diff --git a/pyproject.toml b/pyproject.toml
index 74ff519048..a220457430 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,3 +1,63 @@
+[build-system]
+requires = ["setuptools>=64", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "tensorboard"
+dynamic = ["version", "dependencies"]
+description = "TensorBoard lets you watch Tensors Flow"
+readme = {file = "tensorboard/pip_package/README.rst", content-type = "text/x-rst"}
+requires-python = ">=3.9"
+license = {text = "Apache 2.0"}
+authors = [{name = "Google Inc.", email = "packages@tensorflow.org"}]
+keywords = [
+    "tensorflow",
+    "tensorboard",
+    "tensor",
+    "machine learning",
+    "visualizer",
+]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "Intended Audience :: Education",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: Apache Software License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3 :: Only",
+    "Topic :: Scientific/Engineering :: Mathematics",
+    "Topic :: Software Development :: Libraries",
+    "Topic :: Software Development :: Libraries :: Python Modules",
+]
+
+[project.scripts]
+tensorboard = "tensorboard.main:run_main"
+
+[project.entry-points."tensorboard_plugins"]
+projector = "tensorboard.plugins.projector.projector_plugin:ProjectorPlugin"
+
+[project.optional-dependencies]
+tensorflow = ["tf-nightly"]
+
+[tool.setuptools.dynamic]
+version = {attr = "tensorboard.version.VERSION"}
+dependencies = {file = ["tensorboard/pip_package/requirements.txt"]}
+
+[tool.setuptools.packages.find]
+include = ["tensorboard", "tensorboard.*"]
+exclude = ["tensorboard.pip_package", "tensorboard.pip_package.*"]
+
+[tool.setuptools.package-data]
+tensorboard = ["webfiles.zip"]
+"tensorboard.plugins.projector" = [
+    "tf_projector_plugin/index.js",
+    "tf_projector_plugin/projector_binary.html",
+    "tf_projector_plugin/projector_binary.js",
+]
+
 [tool.black]
 line-length = 80
 target-version = ["py36", "py37", "py38"]