Update numpy requirement from >=2.4.6 to >=2.5.2 in /examples/mcp_server

[dependabot]

Updates the requirements on numpy to permit the latest version.

Release notes

Sourced from numpy's releases.

v2.5.2 (Aug 9, 2026)

NumPy 2.5.2 Release Notes

The NumPy 2.5.2 is a patch release that fixes bugs discovered after the 2.5.1 release. The big news is that it includes wheels for the newly released Python 3.15.0rc1.

This release supports Python versions 3.12-3.15

C API changes

PyArray_StringDTypeObject is opaque under the abi3t stable ABI

The PyArray_StringDTypeObject was accidentally exposed in NumPy 2.5 when targeting the free-threading-compatible stable ABI (Py_TARGET_ABI3T). PyArray_StringDTypeObject is now an opaque struct: extensions compiled that way cannot access its fields, since the struct layout depends on the size of the object header. Any code that accessed PyArray_StringDTypeObject fields in an abi3t build would have crashed, so we are making this API change in a bugfix release.

The NpyString allocator API remains usable by passing the descriptor object pointer, e.g. NpyString_acquire_allocator((PyArray_StringDTypeObject *)descr).

(gh-31771)

Contributors

A total of 16 people contributed to this release. People with a "+" by their names contributed a patch for the first time.

• Abhijeetsingh Meena +
• Charalampos Stratakis
• Charles Harris
• Chris Ninham +
• David Woods
• Geonho +
• Gopu Yeshwanth Reddy +
• Iason Krommydas
• Ijtihed Kilani
• Jelle Zijlstra +
• Joren Hammudoglu
• Kumar Aditya
• Mike Boyle
• Nathan Goldbaum
• Raghuveer Devulapalli
• Sebastian Berg

... (truncated)

Changelog

Sourced from numpy's changelog.

This is a walkthrough of the NumPy 2.4.0 release on Linux, which will be the first feature release using the numpy/numpy-release <https://github.com/numpy/numpy-release>__ repository.

The commands can be copied into the command line, but be sure to replace 2.4.0 with the correct version. This should be read together with the :ref:general release guide <prepare_release>.

Facility preparation

Before beginning to make a release, use the requirements/*_requirements.txt files to ensure that you have the needed software. Most software can be installed with pip, but some will require apt-get, dnf, or whatever your system uses for software. You will also need a GitHub personal access token (PAT) to push the documentation. There are a few ways to streamline things:

• Git can be set up to use a keyring to store your GitHub personal access token. Search online for the details.

Prior to release

Add/drop Python versions

When adding or dropping Python versions, multiple config and CI files need to be edited in addition to changing the minimum version in pyproject.toml. Make these changes in an ordinary PR against main and backport if necessary. We currently release wheels for new Python versions after the first Python RC once manylinux and cibuildwheel support that new Python version.

Backport pull requests

Changes that have been marked for this release must be backported to the maintenance/2.4.x branch.

Update 2.4.0 milestones

Look at the issues/prs with 2.4.0 milestones and either push them off to a later version, or maybe remove the milestone. You may need to add a milestone.

Check the numpy-release repo

... (truncated)

Commits

• 48fecee REL: Prepare for the NumPy 2.5.2 release (#32226)
• ecf599c Merge pull request #32221 from charris/backport-32151
• 3c7ac97 Merge pull request #32220 from charris/backport-32205
• 23b30f4 BUG: avoid segfaults when legacy copyswap slot is not defined (#32151)
• 4964ca8 TYP: isclose shape-typing fix for 2d array-likes (#32205)
• c37ed94 MAINT: Skip limited_api tests on some platforms. (#32214)
• 5cfd73b Merge pull request #32206 from charris/update-cibuildwheel
• d8262bc MAINT: Update cibuildwheel to v4.2.0
• 988d94d Merge pull request #32158 from charris/backport-32133
• b2e4f97 BUG: avoid possible stack overflow in arraydescr_dealloc (#32133)
• Additional commits viewable in compare view

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Keep NumPy compatible with Python 3.11

When users follow the documented example-server installation on Python 3.11, pip cannot resolve this requirement because NumPy 2.5.2 supports only Python 3.12–3.15. This contradicts examples/mcp_server/README.md:29,48-50, which explicitly promises Python 3.11+ support and retains the NumPy 2.4.x line for that reason; keep this dependency on a compatible 2.4.x release, or consistently raise and test the repository's Python floor.

AGENTS.md reference: AGENTS.md:L42-L49

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