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66 changes: 66 additions & 0 deletions .github/workflows/generator-generic-ossf-slsa3-publish.yml
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# This workflow uses actions that are not certified by GitHub.
# They are provided by a third-party and are governed by
# separate terms of service, privacy policy, and support
# documentation.

# This workflow lets you generate SLSA provenance file for your project.
# The generation satisfies level 3 for the provenance requirements - see https://slsa.dev/spec/v0.1/requirements
# The project is an initiative of the OpenSSF (openssf.org) and is developed at
# https://github.com/slsa-framework/slsa-github-generator.
# The provenance file can be verified using https://github.com/slsa-framework/slsa-verifier.
# For more information about SLSA and how it improves the supply-chain, visit slsa.dev.

name: SLSA generic generator
on:
workflow_dispatch:
release:
types: [created]

jobs:
build:
runs-on: ubuntu-latest
outputs:
digests: ${{ steps.hash.outputs.digests }}

steps:
- uses: actions/checkout@v4

# ========================================================
#
# Step 1: Build your artifacts.
#
# ========================================================
- name: Build artifacts
run: |
# These are some amazing artifacts.
echo "artifact1" > artifact1
echo "artifact2" > artifact2
# ========================================================
#
# Step 2: Add a step to generate the provenance subjects
# as shown below. Update the sha256 sum arguments
# to include all binaries that you generate
# provenance for.
#
# ========================================================
- name: Generate subject for provenance
id: hash
run: |
set -euo pipefail
# List the artifacts the provenance will refer to.
files=$(ls artifact*)
# Generate the subjects (base64 encoded).
echo "hashes=$(sha256sum $files | base64 -w0)" >> "${GITHUB_OUTPUT}"
provenance:
needs: [build]
permissions:
actions: read # To read the workflow path.
id-token: write # To sign the provenance.
contents: write # To add assets to a release.
uses: slsa-framework/slsa-github-generator/.github/workflows/generator_generic_slsa3.yml@v1.4.0
with:
base64-subjects: "${{ needs.build.outputs.digests }}"
upload-assets: true # Optional: Upload to a new release
2 changes: 1 addition & 1 deletion README.md
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The GitHub MCP Server connects AI tools directly to GitHub's platform. This gives AI agents, assistants, and chatbots the ability to read repositories and code files, manage issues and PRs, analyze code, and automate workflows. All through natural language interactions.

### Use Cases
### Use Cases

- Repository Management: Browse and query code, search files, analyze commits, and understand project structure across any repository you have access to.
- Issue & PR Automation: Create, update, and manage issues and pull requests. Let AI help triage bugs, review code changes, and maintain project boards.
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