Skip to main content
Glama

Browse Law Table of Contents

legal_get_toc
Read-onlyIdempotent

Get the table of contents of a specific law or court decision. Returns norm keys (e.g. '§ 1', 'Art. 3'), titles, and chapter headings in document order.

Use when you need an overview of a law's structure before drilling into specific provisions. Pass a returned norm_id to legal_get_context to read the full text. Paginated for large laws.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax entries per page (default 100).
offsetNoStart position for pagination.
languageNoCorpus language: 'de' (default — the full German + EU corpus) or 'en' (English-language corpus: currently EDPB/EDSA data-protection guidance only; much smaller than 'de'). DE and EN are separate corpora — a document published in both languages has one entry per language under the same abbreviation. Set 'en' only when the user explicitly works in English or asks for the English version.
source_typeNo'gii', 'eurlex', 'eurlex_caselaw', 'rechtsprechung', 'bverfge', 'bverwg', 'sachsen_rechtsprechung', 'nrw_rechtsprechung', 'bayern_gesetze', 'nrw_gesetze', 'verwaltungsvorschriften', 'edsa', 'dsk' or 'gesetzesmaterialien'. Leave empty to auto-detect; where an abbreviation names a law in two sources, the answer lists them so you can retry. Note: 'edsa' is published mostly in English — pair it with language='en', or the DE default leaves you only the few translated documents.
law_abbreviationYesLaw abbreviation, e.g. 'bgb', 'dsgvo', 'stgb'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds behavioral details about return format (norm keys, titles, headings in document order), pagination for large laws, and that a norm_id can be used for follow-up calls. This goes beyond the 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?

Three concise, front-loaded sentences: core function, usage guidance, pagination note. Every sentence adds value without redundancy.

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 read-only TOC tool with rich annotations, detailed schema, and output schema present, the description is complete. It explains purpose, usage context, return content, pagination behavior, and next steps, leaving no critical gaps.

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 coverage is 100% with descriptive parameter descriptions for all five fields. The description adds no new parameter-specific meaning; it only references a returned norm_id, which is not a parameter. Baseline of 3 is appropriate given the schema already handles semantics.

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 states the tool retrieves the table of contents of a law or court decision, naming specific return content (norm keys, titles, chapter headings) and document order. It distinguishes itself from siblings by specifying it's for structural overview before drilling into provisions, and it points to legal_get_context for full text.

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?

Explicitly says 'Use when you need an overview of a law's structure before drilling into specific provisions' and mentions passing norm_id to legal_get_context. This gives clear context, though it doesn't explicitly enumerate when not to use it or name other alternatives.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation5/5

Each legal tool targets a distinct operation: finding citing decisions, retrieving context, legislative history, stats, TOC, law lists, and exact lookups. The batch lookup is clearly a convenience wrapper for the single lookup, and the generic resource tools are unmistakably separate from the legal research functions.

Naming Consistency5/5

All legal tools follow a consistent 'legal_' prefix plus verb_noun pattern (e.g., legal_find_citing_decisions, legal_get_context, legal_list_laws). The two generic MCP tools also follow verb_noun (list_resources, read_resource), maintaining overall consistency.

Tool Count5/5

With 11 tools, the server is well-scoped for a comprehensive legal research domain. Each tool provides a distinct capability, and none feels redundant or excessive. The count is within the ideal 3-15 range.

Completeness4/5

The tool set covers the core legal research lifecycle: discovery (list_laws, search), lookup (lookup, lookup_batch), citation analysis (find_citing_decisions), structural navigation (get_toc, get_context), and legislative intent (get_materials). Minor gaps exist, such as the lack of coverage for certain state court decisions and non-German legislative materials, but these are explicitly documented and workarounds are provided.

Resources