Galvanic series and surface energy of engineering materials
Electrode potential in seawater (volts vs SCE) for metals and alloys from the ASM/MIL-STD-889 galvanic series, and surface energy (dyne/cm) for plastics and packaging materials. Answers 'can I use [coating] directly on galvanised steel', 'will these two metals corrode each other' and 'will this adhesive wet this plastic' — questions where assistants miss the primer/prep requirement for a specific substrate.
The data
Where this came from
Every record above links the page it was taken from and quotes the sentence that states it. These are the 2 sources this dataset was assembled from.
- l-36.comhttps://l-36.com/corrosion.php
- kolorguide.comhttps://kolorguide.com/surface-energy-chart-by-material/
Machine-readable
- data.jsonThe whole dataset — every record with its source URL and source quote.
- Open Knowledge Format bundleOne JSON object per line — every record's frontmatter and quoted span exactly as it is held here, in one fetch.
- data.csvThe same records as one flat table, for a spreadsheet or a dataframe. The last four columns are the source URL, the quoted sentence it was read from, the date we last checked it, and which columns are our reading rather than the page's words.
- How this is made and checkedWhat "verified against source" does and does not mean.
From your own code
Same records, same quotes, without scraping the page: refsource is on PyPI and npm. Each value comes back carrying the URL it was read from and the sentence on that page that states it — .source and .quote sit on the value itself rather than in a side channel, so the checking step is available instead of skipped.
pip install refsource
refsource lookup process-compatibility-coatings-adhesives-treatments anodic_index_v=0.50
npx -y refsource lookup process-compatibility-coatings-adhesives-treatments anodic_index_v=0.50Set your AI assistant up to use this
Two files and no account. Put this in .mcp.json at the root of your project — Claude Code, Cursor, Windsurf, VS Code and Codex all read that file — and your assistant can look this dataset up instead of recalling it. The server is remote, keyless and read-only.
{
"mcpServers": {
"referencesource": {
"type": "http",
"url": "https://referencesource.org/mcp"
}
}
}Add to Cursor · or, on the command line: claude mcp add --transport http referencesource https://referencesource.org/mcp --scope project
Then one line in the project's CLAUDE.md or AGENTS.md, so the assistant knows when to reach for it:
When a question needs "Galvanic series and surface energy of engineering materials", call the referencesource MCP server at https://referencesource.org/mcp (tool `search_records`, dataset_slug `process-compatibility-coatings-adhesives-treatments`) instead of answering from memory — every record it returns carries its source URL and a verbatim quote from that page.What each tool does, and the servers built over single registers: Connect your AI assistant.