INDIVIDUAL MCP TOOL

get_record_format

A record serialised as schema.org, Croissant, RO-Crate, FAIR Data Point DCAT3, enriched DataCite, or the GDS AI-readiness assessment.

fairdata.ainone authenticationAvailability not checked

LIVE ENDPOINT

https://fairdata.ai/api/mcp

No auth detected

Connect to this endpoint to inspect the live schema for get_record_format and invoke it with your own arguments.

{}

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_ruleset — The qualification ruleset in force: every criterion, its threshold, the evidence type behind it, what an unknown value means, and the limits of the verdict.
search_collections — Find themed collections of research datasets.
get_collection — One collection in full: what it is, what defines membership, its aggregates, its licence position, its freshness, and where to fetch it in each available format.
compare_collections — Compare two to five collections on the dimensions that decide whether one is usable for a task: size, licence clarity and mix, FAIR and curation medians, file accessibility, assessment freshness, and modality coverage.
list_collection_datasets — The member datasets of a collection, with licence, scores, file counts and links.
get_collection_manifest — The versioned manifest for a collection — the artefact to pin a workflow to.
explain_collection_qualification — The full criteria matrix for a collection: each criterion, its threshold, the observed value, pass/fail/unknown, and the evidence with its evaluator and version.
search_datasets_in_corpus — Keyword search over the datasets that clear the Machine-Ready gate.