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oyez-mcp

by attorneynate
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Get a Supreme Court case

get_case
Read-onlyIdempotent

Look up one Supreme Court case by term and docket to get parties, citation, key dates, decision, vote breakdown, opinion authors, advocates, and audio.

Instructions

Full details for one Supreme Court case: parties, citation, key dates, facts, the question presented, the holding/conclusion, the decision with its vote breakdown and opinion authors, the advocates, and a list of the available oral-argument and opinion-announcement audio.

"Written opinions" links each opinion's text on Justia: the syllabus, the opinion of the Court, and every concurrence and dissent, by author.

The "Links" line is the address to cite or open. Take it as printed rather than building one from the Term and docket: oyez.org serves the same single-page shell for every path under /cases/, so a composed address that is wrong still answers 200 and renders an empty page.

Args: term: The Term year, e.g. "2014" (from search_cases). docket: The docket number, e.g. "14-556" (from search_cases). Older cases sit in bucketed Terms (1789-1850, 1850-1900, 1900-1940, 1940-1955) where Oyez addresses a case by volume-us-page instead, e.g. term "1940-1955", docket "347us483" for Brown. The docket number search_cases printed is tried first and usually works; when two cases share one, the error names both addresses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
termYes
docketYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint), yet the description adds real operational context: a warning that composing an oyez.org address can silently render an empty 200 page, and the disclosure that duplicate docket numbers produce an error naming both candidate addresses. It stops short of return-shape or pagination detail, but the failure-mode disclosure is unusually valuable.

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

Conciseness4/5

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

Front-loads the return contents, then the citation caveat, then the args, which is a sensible order for an agent. The prose is information-dense but the paragraph on the 'Links' line and the bucketed-Terms passage are both slightly long for the payload they carry.

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

Completeness4/5

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

With no output schema, the description carries the return-value burden and does so by enumerating the case fields and the linked opinion texts. Arguments are fully specified for a 0%-coverage schema. Minor gaps remain around not-found handling and audio payload specifics, but nothing blocks a correct call.

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

Parameters5/5

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

Schema coverage is 0% and the two properties carry no descriptions, so the description must compensate and does: it gives the term format ('2014'), the docket format ('14-556'), explains the bucketed Terms (1789-1850 through 1940-1955) where volume-us-page addressing is used, and describes retry/fallback behavior on duplicate dockets.

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?

States a specific verb and resource ('Full details for one Supreme Court case') and then enumerates exactly what is returned: parties, citation, dates, facts, question presented, holding, vote breakdown, opinion authors, advocates, and audio. An agent can tell this apart from search_cases or get_oral_argument without opening a schema.

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?

Clearly indicates the inputs come from search_cases and gives an explicit fallback path for older bucketed Terms, including the Brown / '347us483' example. It does not, however, state explicit when-not-to-use conditions or contrast itself against get_opinion_announcement or get_oral_argument, which also surface audio.

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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