fedlex.list_versions
List every dated consolidation (Fassung) of an act, future ones included: use to pick the eli_version the reading tools need. norm.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| eli | Yes | Fedlex ELI of the consolidation abstract. |
List every dated consolidation (Fassung) of an act, future ones included: use to pick the eli_version the reading tools need. norm.
| Name | Required | Description | Default |
|---|---|---|---|
| eli | Yes | Fedlex ELI of the consolidation abstract. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint=true, the safety profile is already disclosed; the description adds the useful behavioral detail that future consolidations are returned. It does not disclose ordering, pagination, or return shape, which keeps it at an adequate but not rich level.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The core guidance is one front-loaded sentence with useful context. The trailing 'norm.' is stray and unexplained, which prevents a perfect score, but there is no other waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, read-only listing tool, the description covers what the tool returns, that future versions are included, and how to use the result (pick eli_version). It is complete enough for selection and invocation, though a short note on output items would make it fully robust.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema describes the single 'eli' parameter and schema description coverage is 100%, so the baseline applies. The description does not add extra detail about the ELI format or the relationship between a consolidation abstract and an act, but it also does not need to because the schema covers the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with a precise resource ('dated consolidation (Fassung) of an act') and explicitly notes future versions are included. It also ties the purpose to picking an eli_version for reading tools, which distinguishes it from related tools like fedlex.read_document or fedlex.list_expressions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives a clear usage context: use this before reading tools to select the eli_version. It does not name alternatives or state when not to use it, but the workflow guidance is explicit enough for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The tools are strongly namespaced and most have a clear 'use for' hint, so an agent can usually select correctly. A few near-neighbour pairs, such as fedlex.get_citations vs fedlex.get_references and facts.badge vs facts.latest, require careful reading but are still distinguishable.
The <domain>.<snake_case_action> style is consistent and the fedlex/lindas families are predictable. However, several noun-style names such as meta.tools, lindas.observations, and facts.badge deviate from the verb_noun pattern, and the variety of get_/read_/list_/find_ verbs adds minor noise.
With 52 tools, this is a very large MCP surface for one server; while each tool appears individually purposeful, the combined set is heavy for an agent to explore and select from. The gateway would be more manageable split into separate legal, data, and meta servers.
The Fedlex cluster covers the full legal-research workflow: search, version resolution, reading, comparison, citation checking, history tracing, consultations, and official publications. The LINDAS cluster covers cube discovery, schema inspection, filtering, and label resolution, and the directory/meta tools complete the capability-discovery loop. There are no obvious dead ends or critical missing operations.