{
"mcpServers": {
"prow-mcp-server": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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Prow CI MCP Server
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
License not specified.
Is it maintained?
Last commit 13 days ago. 5 stars.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
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Privacy-first. MCP is the protocol for tool access. We're the virtualization layer for context.
Pre-build reality check. Scans GitHub, HN, npm, PyPI, Product Hunt — returns 0-100 signal.
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A Model Context Protocol (MCP) server for interacting with Prow CI/CD systems, retrieving build logs, and diagnosing PR build issues.
The server exposes 7 MCP tools:
get_latest_job_run - Get the latest job run information for a specific job nameget_job_logs - Retrieve logs for a specific Prow job IDget_build_logs - Get logs for a specific build ID and job nameget_latest_prow_build_for_pr - Find the latest Prow build for a GitHub PRget_prow_logs_from_pr - Get comprehensive logs for a specific PRdiagnose_pr_build_status - Comprehensive diagnostic tool for PR build issuesget_test_failures_from_artifacts - Extract test failures from build artifactsCheck out the examples directory.
cd /path/to/prow-mcp-server
uv sync # Creates venv and installs dependencies from uv.lock
source .venv/bin/activate # On Windows: .venv\Scripts\activate
Add to your ~/.cursor/mcp.json:
{
"mcpServers": {
"prow": {
"command": "uv",
"args": ["run", "/path/to/prow-mcp-server/.venv/bin/python", "/path/to/prow-mcp-server/main.py"],
"description": "MCP server for Prow CI/CD integration"
}
}
}
For web applications or services that need HTTP-based communication:
{
"mcpServers": {
"prow": {
"url": "http://0.0.0.0:8000/sse/",
"description": "MCP server for Prow CI/CD integration with direct SSE",
"env": {
"MCP_TRANSPORT": "sse"
}
}
}
}
SSE Endpoint: http://0.0.0.0:8000/sse/
Note: Make sure to start the SSE server separately with
MCP_TRANSPORT=sse uv run main.pybefore using this configuration.
Run the comprehensive test suite (18 tests):
uv run python run_tests.py # Recommended
uv run pytest tests/ -v # Direct pytest
All tests pass in under 0.25 seconds with full coverage of utilities, services, and MCP tools.
The server uses a modular architecture with clear separation of concerns:
mcp_server/
├── main.py # Server entry point
├── config.py # Configuration
├── models/ # Type definitions
├── utils/ # Helper functions
├── services/ # Business logic (Prow API, GCS)
└── tools/ # MCP tool implementations
The server uses intelligent fallback strategies to find PR builds:
For standard MCP integration with Cursor IDE:
# Build
podman build -t prow-mcp:latest .
# Run
podman run -i --rm prow-mcp:latest
# MCP Config
{
"mcpServers": {
"prow-server": {
"command": "podman",
"args": ["run", "-i", "--rm", "localhost/prow-mcp:latest"]
}
}
}
For web-based integrations and HTTP communication:
# Build SSE container
podman build -f Containerfile.sse -t prow-mcp-sse:latest .
# Run SSE container
podman run -p 8000:8000 --rm prow-mcp-sse:latest
# MCP Config
{
"mcpServers": {
"prow-sse": {
... [View full README on GitHub](https://github.com/redhat-community-ai-tools/prow-mcp-server#readme)