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eur-lex-mcp-server

by io.github.cyanheads

Resolve EU Legal Citation

eurlex_lookup_celex
Read-onlyIdempotent

Resolve an EU legal citation — a CELEX number or ELI URI — to its canonical CELLAR work, confirming it exists before you fetch or traverse it. Returns the work URI, confirmed CELEX number, document type, and date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
identifierYesThe EU legal citation to resolve: a CELEX number (e.g. 32016R0679) or a work-level ELI URI (e.g. http://data.europa.eu/eli/reg/2016/679, with or without the /oj suffix).
identifier_typeNoFormat of the identifier. "auto" detects it automatically; supply "celex" or "eli" explicitly if detection fails.auto

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoDocument date in ISO 8601 format (YYYY-MM-DD).
errorNoPresent when the call failed. Absent on success.
foundNoTrue when the identifier resolves to a CELLAR work; false when a well-formed CELEX/ELI matches no work in the corpus. A malformed or undetectable identifier raises ambiguous_identifier instead.
work_uriNoCELLAR work URI (stable resource identifier).
celex_numberNoConfirmed CELEX number for the resolved work.
resource_typeNoCDM resource type URI indicating the document category (e.g. .../resource-type/REG for Regulation). Absent for some works.

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable behavioral context: it confirms existence, returns a canonical/confirmed resolution, and lists the specific return fields. It does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the first sentence states the core purpose and usage, and the second lists the key return values. Every clause earns its place with no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter resolution tool with rich annotations and an output schema, the description fully covers what an agent needs: what to pass, why to call it, when to call it, and what to expect back. No critical contextual gap remains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents both parameters. The description's mention of CELEX/ELI inputs mirrors the schema rather than adding new meaning. A baseline score of 3 is appropriate since the schema carries the semantic load.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action ('Resolve'), the input (CELEX number or ELI URI), and the output (canonical CELLAR work URI, confirmed CELEX, document type, date). It also distinguishes the tool from siblings by framing it as a pre-flight confirmation step before fetching or traversing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: use this tool when you need to confirm an EU legal citation exists and resolve it before fetching or traversing. It does not explicitly name sibling alternatives or state when not to use it, but the intended placement in a workflow is evident.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: subject browsing, case search, document retrieval, relation traversal, identifier resolution, raw SPARQL, and legislation search. The few potentially similar tools (search_documents vs get_cases) are clearly separated by corpus and description.

Naming Consistency5/5

All tools follow the consistent eurlex_verb_noun pattern in lowercase snake_case, such as eurlex_get_document, eurlex_search_documents, and eurlex_lookup_celex. Verbs vary but the pattern is uniform and predictable.

Tool Count5/5

Seven tools is well-scoped for an EU legal research server covering search, retrieval, relationship traversal, and identifier resolution. Each tool has a clear role and none feel redundant or excessive.

Completeness4/5

The core research workflow is covered: browse subjects, search legislation, search cases, fetch documents, resolve identifiers, and traverse relations. Minor gaps exist such as no full-text body search and no explicit case-law full-text retrieval, but the raw SPARQL escape hatch partially mitigates these.

Resources