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jimdawdy-hub

freecase-mcp

by jimdawdy-hub

search_cases

Find relevant case law from Illinois, federal, SCOTUS, and 7th Circuit courts using natural language queries, citations, or Boolean operators. Apply filters for jurisdiction, date range, and precedential status.

Instructions

Search the Freecase case-law corpus (Illinois, federal, SCOTUS, 7th Circuit).

Requires a Freecase connector key in the FREECASE_MCP_KEY environment variable; without one, this tool returns an error explaining how to set it.

Returns the query echoed back, candidate/return counts, whether AI reranking ran, and a results array. Each result mirrors the Freecase API fields exactly (case_name, court_full, date_filed, snippet, treatment_status, cluster_id, etc.). The score field is Freecase's own opaque combined ranking score (a weighted mix of text relevance, court authority, recency, and citation count) — it is NOT a normalized 0-1 relevance value; use it only to compare results within one response. Pass a result's cluster_id to get_opinion to read the full text.

Args: q: The search query (see field description — forwarded unchanged). jurisdiction: Court scope to search within. date_from: Earliest decision date (YYYY-MM-DD). date_to: Latest decision date (YYYY-MM-DD). precedential: Exclude unpublished/errata opinions (default true). rerank: Enable AI reranking (slower, AI-metered; default false). fast: Use the faster rerank model (only when rerank is true). limit: Maximum number of results (1-200; default 25).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesThe search query, forwarded to Freecase as-is. Freecase detects reporter citations (e.g. '410 U.S. 113'), case names, keywords, and Boolean/proximity operators server-side — do not pre-parse or rewrite the query.
fastNoWhen reranking, use the faster/cheaper model. Ignored if rerank is false.
limitNoMaximum results to return (1-200). Defaults to 25.
rerankNoRun the AI reranker over the results for better ordering. Slower (can take up to ~90s) and metered as AI-assisted use, so it is off by default — turn it on only when ranking quality matters.
date_toNoLatest decision date, YYYY-MM-DD. Omit for no upper bound.
date_fromNoEarliest decision date, YYYY-MM-DD. Omit for no lower bound.
jurisdictionNoOne of: 'all', 'il' (Illinois), 'federal', 'scotus' (U.S. Supreme Court), 'ca7' (7th Circuit).all
precedentialNoExclude unpublished/errata opinions. Defaults to true.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. It explains the need for an environment variable, the return structure including score meaning, and AI reranking behavior (slower, metered). It is thorough in disclosing the tool's dependencies and outputs.

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?

The description is front-loaded with purpose and requirements, then covers return structure and parameters. It is somewhat verbose but well-organized; each sentence adds information.

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?

The description covers prerequisites, return structure, and parameter details. With an output schema existing, the explanation is sufficient. Missing explicit error handling or rate limiting, but overall comprehensive for a search tool.

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%, so baseline is 3. The description adds marginal value by mentioning not to pre-parse the query and listing jurisdiction examples, but largely repeats schema descriptions.

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 it searches the Freecase case-law corpus with specific courts listed. It distinguishes from siblings like get_opinion and search_statutes by mentioning that get_opinion retrieves full text using cluster_id.

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 provides context on when to use rerank and indicates that get_opinion should be used for full text. It implicitly differentiates from statute searching by the sibling tool search_statutes. However, it does not explicitly state when not to use this tool.

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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