INDIVIDUAL MCP TOOL

get_files

Get the direct, downloadable files for a dataset — real contentUrl + size + checksum per file, resolved from the source repository.

fairdata.ainone authenticationAvailability not checked

Input schema

{}

Inferred read-only · medium confidence · heuristic, not a guarantee.

No write-capable action terms were found; this is not proof that invocation has no side effects.

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.fairdata-ai]
url = "https://fairdata.ai/api/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "fairdata-ai": {
      "type": "http",
      "url": "https://fairdata.ai/api/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: fairdata-ai
Remote MCP URL: https://fairdata.ai/api/mcp

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "fairdata-ai": {
      "url": "https://fairdata.ai/api/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "fairdata-ai": {
      "type": "http",
      "url": "https://fairdata.ai/api/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "fairdata-ai",
  "transport": "streamable-http",
  "url": "https://fairdata.ai/api/mcp"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

get_record — Retrieve the FAIRdata.ai enriched record for a research dataset DOI.
get_record_format — Get a FAIRdata.ai enriched record serialised in a specific machine-actionable format.
assess_dataset — Run a full FAIR and AI-readiness assessment for a research dataset by DOI.
list_records — Browse the FAIRdata.ai record registry.
get_ai_readiness — Get a detailed AI-readiness assessment for a dataset against the GDS/DSIT 4-pillar framework ('Making Government Datasets Ready for AI', January 2026).
get_data_quality — Get a schema-level data-quality grade (0-100) for a dataset's tabular files: completeness (non-null), structure (non-constant columns), and size.
find_training_data — Find AI-ready datasets for model training/evaluation by theme.
find_similar_datasets — Find datasets most similar to a given DOI by cosine similarity over pre-computed 768-dim text embeddings (title + description, OpenAI text-embedding-3-small).