CRED-1

CRED-1: Open Domain Credibility Dataset

CRED-1 is an open, reproducible domain-level credibility dataset combining multiple openly-licensed source lists with computed enrichment signals. It provides credibility scores for 2,600+ domains (exact count in the latest release) known to publish mis/disinformation, conspiracy theories, or other unreliable content. Community members can report missing domains for inclusion.

🎓 Presented at ACM WebSci 2026 (Braunschweig). Landing page: aloth.github.io/agentic-ai-information-integrity/cred-1.

🤖 MCP-ready — query domain credibility directly from Claude Desktop, Cursor & Windsurf, or any MCP-compatible agent. Jump to setup ↓

Paper: A. Loth, M. Kappes, and M.-O. Pahl, "CRED-1: An Open Multi-Signal Domain Credibility Dataset for Automated Pre-Bunking of Online Misinformation," *Preprint*, 2026. doi:10.2139/ssrn.6448466

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Install

# CLI (global)

npm install -g @aloth/cred1

Library (project dependency)

npm install @aloth/cred1

Or try without installing

npx @aloth/cred1 check infowars.com

CLI Usage

# Single domain lookup

cred1 check infowars.com

🔴 infowars.com

Score: 0.073 / 1.000

Category: conspiracy

Level: low

Sources: 2

Domain not in dataset

cred1 check nytimes.com

⚪ nytimes.com

Not found in CRED-1 dataset — treat as unknown/neutral

Batch processing (stdin)

echo -e "rt.com\ninfowars.com\nnytimes.com" | cred1 batch

JSON output

cred1 check breitbart.com --json

Search

cred1 search "news" cred1 search "\.ru$"

Statistics

cred1 stats cred1 categories

Domain normalization is automatic — https://www.infowars.com/politics/ resolves to infowars.com.

MCP Server (Claude Desktop / Cursor / Windsurf)

CRED-1 ships an MCP server so AI assistants can check domain credibility directly.

Tools exposed

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{

"mcpServers": { "cred1": { "command": "npx", "args": ["-y", "@aloth/cred1", "--mcp"] } } }

Note: --mcp is handled by the CLI wrapper — or run the dedicated binary directly.

Alternatively, if the package is installed globally:

{

"mcpServers": { "cred1": { "command": "cred1-mcp" } } }

Cursor

Add to .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{

"mcpServers": { "cred1": { "command": "npx", "args": ["-y", "@aloth/cred1", "--mcp"] } } }

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{

"mcpServers": { "cred1": { "command": "npx", "args": ["-y", "@aloth/cred1", "--mcp"] } } }

OpenClaw / any MCP-compatible host

{

"command": "cred1-mcp", "transport": "stdio" }

Pinning a version

With npx -y @aloth/cred1, npx checks npm for a newer version each time the host starts the server and installs it, and a new version is published every week. A host restart can therefore run a release you have not reviewed. To decide when to update, pin the version in the config:

{

"mcpServers": { "cred1": { "command": "npx", "args": ["-y", "@aloth/cred1@2026.10.27", "--mcp"] } } }

Or install a fixed version globally and point the host at the cred1-mcp binary as shown above:

npm install -g @aloth/cred1@2026.10.27

Replace 2026.10.27 with the version you reviewed; npm view @aloth/cred1 version prints the latest one.

Most weekly releases only refresh the bundled dataset (data/cred1_compact.json), but every release is built from the current main branch, so code changes ship the same way. To see what changed between two versions, compare their tags, for example v2026-10-20...v2026-10-27. The server reads the dataset from the installed package and makes no network requests. Since 2026.6.14, releases are published from GitHub Actions with npm provenance, which npm audit signatures verifies.

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Library Usage

import { checkDomain, searchDomains, getStats } from '@aloth/cred1';

// Single lookup const result = checkDomain('infowars.com'); // { domain: 'infowars.com', score: 0.073, category: 'conspiracy', level: 'low', sources: 2, domainAge: 27.3, trancoRank: 15889 }

// Not found → null const unknown = checkDomain('nytimes.com'); // null

// Search by pattern (substring or regex) const russian = searchDomains('\\.ru$');

// Dataset statistics const stats = getStats(); // { totalDomains: 2673, categories: { unreliable: 2001, fake: 233, ... }, version: '1.0.0' }

Traffic-Light Scoring

Key Features

• 2,674 domains with credibility scores (0.0–1.0)
• Dual-mode — works as CLI tool and JavaScript library
• Fully reproducible — Python pipeline rebuilds the dataset from scratch
• Multi-signal scoring combining source labels, domain age, web popularity, fact-check frequency, and threat intelligence
• Privacy-preserving — designed for on-device client-side deployment (no server calls needed)
• Two openly-licensed sources — no proprietary data dependencies
• Domain normalization — handles www., protocols, paths automatically

Dataset Schema

Compact Format (cred1_compact.json)

{

"infowars.com": { "c": "c", "s": 0.073, "n": 2, "d": "1999-10-04", "r": 15889 } }

Full Format (cred1_current.json)

{

"infowars.com": { "category": "fake", "credibility_score": 0.14, "domain_age_years": 26.4, "domain_registered": "1999-10-04T04:00:00Z", "iffy_factual": "VL", "iffy_bias": "FN", "iffy_score": 0.1, "factcheck_claims": 52, "safe_browsing_flagged": false, "score_age": 0.2, "score_cat": 0.05, "score_factcheck": 0.0, "score_iffy": 0.1, "score_safebrowsing": 0.05, "score_tranco": 0.1, "sources": 2, "tranco_rank": 4382 } }

See CODEBOOK.md for full field documentation.

What the score is, and what it is not

The credibility score is a domain-level signal, not an item-level verdict. It says how a source has been rated by public source-rating initiatives; it does not say whether any individual article is true. Research that uses it as a veracity label is therefore working with a provenance-implied rather than item-verified signal: material drawn from domains scoring below 0.25 can be labelled low-credibility, material from established outlets legitimate, but no single item has been fact-checked. Outlet reputation is a good but imperfect proxy, and that bound should be carried into any reuse.

Rebuilding the Dataset

cd pipeline/

python3 build_dataset.py # Full pipeline python3 build_dataset.py --step fetch # Download raw data only python3 build_dataset.py --step merge # Parse + merge (requires prior fetch) python3 enrich_dataset.py # Add enrichment signals (API keys required)

Versioning

CRED-1 uses calendar versioning (CalVer) across all distribution channels:

A new version is released weekly with rescored domains. The npm package updates automatically with each GitHub release — no separate version scheme needed.

To pin a specific dataset version:

npm install @aloth/cred1@2026.6.13

Production Integrations

• [Trackless Links](https://github.com/aloth/trackless-links) — Safari extension for iOS and macOS that checks links locally against CRED-1 (reviewed in Mac & i 4/2026)
• [RogueGPT](https://github.com/aloth/RogueGPT) — Uses CRED-1 to identify low-credibility source domains for controlled fake-news stimulus generation
• [HuggingFace](https://huggingface.co/datasets/xlth/CRED-1) — Dataset mirror for ML pipelines

Contributing

Know a domain that should be in the dataset? Report a missing domain with evidence.

We accept community-reported domains that meet at least one of these criteria:

• Listed by Media Bias/Fact Check (MBFC)
• Flagged by an IFCN-certified fact-checker
• Subject to press council or regulatory action
• Documented in Wikipedia with credibility concerns
• Referenced in published academic research

Accepted domains are added to the pipeline and appear in the next weekly dataset release.

Citation

If you use CRED-1 in your work, please cite both the paper and the dataset version you used. The paper describes the method; the Zenodo record pins the exact data, which is what makes your results reproducible.

Paper:

@misc{loth2026cred1,

author = {Loth, Alexander and Kappes, Martin and Pahl, Marc-Oliver}, title = {{CRED-1}: An Open Multi-Signal Domain Credibility Dataset for Automated Pre-Bunking of Online Misinformation}, year = {2026}, howpublished = {Preprint}, doi = {10.2139/ssrn.6448466}, url = {https://ssrn.com/abstract=6448466}, urldate = {2026-08-25} }

Dataset:

@dataset{loth2026cred1data,

author = {Loth, Alexander}, title = {{CRED-1}: An Open Multi-Signal Domain Credibility Dataset}, year = {2026}, publisher = {Zenodo}, version = {v2026-03-17}, doi = {10.5281/zenodo.18769459}, url = {https://doi.org/10.5281/zenodo.18769459} }

The DOI above always resolves to the latest release. To cite a specific weekly sna