entscheidsuche.ch 스위스 법률 결정 검색 API에 접속하기 위한 MCP 서버입니다.
이 서버는 모델 컨텍스트 프로토콜(MCP)을 통해 스위스 법원 판결에 대한 표준화된 접근을 제공합니다. Claude와 같은 LLM은 이를 통해 entscheidsuche.ch 데이터베이스에서 법률 문서를 검색, 조회 및 분석할 수 있습니다.
Related MCP server: Legal Court MCP Server
리소스 : 스위스 법원 판결을 검색 가능한 리소스로 활용하세요
도구 : 법원 판결 검색, 문서 검색, 주별 법원 목록
프롬프트 : 일반적인 법률 연구 작업을 위한 템플릿
지엑스피1
Claude for Desktop 설정 열기
claude_desktop_config.json 에 다음을 추가하세요.
{
"mcpServers": {
"entscheidsuche": {
"command": "node",
"args": ["/absolute/path/to/entscheidsuche-mcp-server/build/index.js"]
}
}
}데스크톱용 Claude를 다시 시작하세요
법률 연구 질문을 시작해 보세요!
npx @modelcontextprotocol/inspector node /path/to/entscheidsuche-mcp-server/build/index.jsentscheidsuche://scrapers - 사용 가능한 모든 스크래퍼/컬렉션을 나열합니다.
entscheidsuche://scraper/{scraperId} - 특정 스크래퍼에 대한 세부 정보를 가져옵니다.
entscheidsuche://document/{documentId} - 특정 문서의 메타데이터에 액세스합니다.
search-decisions - Elasticsearch 쿼리 구문을 사용하여 법원 판결 검색
get-document-content - 특정 문서의 내용을 검색합니다.
list-courts - 주별로 이용 가능한 법원 목록
get-document-urls - 문서의 PDF 및 HTML 버전에 대한 직접 URL을 가져옵니다.
search-legal-precedents - 특정 법률 주제에 대한 관련 선례 찾기
compare-jurisdictions - 여러 주에서 특정 법률 문제에 대한 판결을 비교합니다.
court-decisions - 특정 법원의 최근 판결 검색
Can you find Swiss court decisions about copyright infringement in Zurich from the last 5 years?How do different Swiss cantons approach the legal issue of tenant rights in rental disputes?Can you retrieve and analyze the decision with ID "ZH_VG-VB.2021.00042"?MCP TypeScript SDK로 구축됨
"entscheidsuche.ch 서버에 친절하기 위해" 요금 제한을 존중합니다.
적절한 인증 및 오류 처리를 처리합니다.
주요 메타데이터(법원, 날짜, 사건 번호)를 사용하여 검색 결과 형식을 지정합니다.
기여를 환영합니다! 풀 리퀘스트를 제출해 주세요.
이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다.
API를 제공해 주신 entscheidsuche.ch 에게 감사드립니다.
탁월한 SDK를 제공한 Model Context Protocol 팀에게 감사드립니다.
이 문서에서는 Claude를 통해 Entscheidsuche MCP 서버를 사용하여 스위스의 법적 판결을 조사하는 방법에 대한 예를 제공합니다.
Find Swiss court decisions about intellectual property rights in the technology sector from the last 5 years.What are some important court decisions from the canton of Zurich (ZH) related to landlord-tenant disputes?Can you find Swiss Federal Supreme Court cases discussing the concept of "good faith" (Treu und Glauben) in contract law?Can you retrieve and analyze the Swiss court decision with ID "CH_BGer-4A_283_2021"?I'd like to access the original court decision for case number "ZH_OG-LB190025". Can you provide the PDF and HTML links?How do the cantons of Geneva (GE), Vaud (VD), and Zurich (ZH) differ in their approach to divorce settlements? Please search for relevant cases and compare.Has there been an evolution in how Swiss courts have interpreted data protection rights over the last decade? Search for relevant cases and analyze the trend.I'm researching a case where an employee was terminated while on medical leave. Can you find Swiss court decisions that established precedent for similar situations?Find the most significant Swiss court decisions related to pharmaceutical patent disputes and analyze how they've shaped the legal landscape in this area.Using the compare-jurisdictions prompt, please analyze how different Swiss cantons approach the legal issue of "non-compete clauses" in employment contracts.Using the search-legal-precedents prompt, find relevant Swiss legal precedents about "algorithmic decision making" and data protection, focusing on federal court decisions.Using the court-decisions prompt, retrieve recent decisions from the Swiss Federal Supreme Court (Bundesgericht) within the last 2 years related to cryptocurrency regulation.Retrieve the full content of a specific legal document
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Document format to retrieve | json |
| signature | Yes | Document signature (e.g., CH_BGer_005_5F-23-2025_2025-07-01) | |
| spider | No | Court/spider name (e.g., CH_BGer). If not provided, will be extracted from signature |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Retrieve' implies a read operation, it doesn't disclose important behavioral aspects like authentication requirements, rate limits, error conditions, response format, or whether this is a simple fetch versus a complex operation. The description is minimal and lacks operational context.
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 description is extremely concise - a single sentence that directly states the tool's purpose. There's no wasted language, repetition, or unnecessary elaboration. It's front-loaded with the core functionality.
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 tool with 3 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a valid document signature, how the retrieved content is structured, error handling, or operational constraints. The minimal description leaves too many questions unanswered for effective tool usage.
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?
With 100% schema description coverage, the schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema - it doesn't explain the relationship between signature and spider parameters, provide examples of valid signatures, or clarify the format parameter's implications.
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 clearly states the action ('Retrieve') and resource ('full content of a specific legal document'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'search_case_law' or 'list_courts' - it doesn't explain that this retrieves a single document by signature rather than searching or listing.
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?
The description provides no guidance about when to use this tool versus alternatives. There's no mention of prerequisites, when this tool is appropriate versus 'search_case_law', or any context about what constitutes a 'specific legal document' that can be retrieved.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get information about available courts and their document counts
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions 'Get information' but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what format the information is returned in. The description is minimal and lacks essential context for safe invocation.
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 description is a single, efficient sentence that directly states the tool's purpose without any fluff or unnecessary details. It is front-loaded and appropriately sized for a simple tool with no parameters.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'information' includes (e.g., court names, IDs, document counts), how results are structured, or any limitations. For a tool that returns data, more context is needed to guide the agent effectively.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and since there are none, it meets the baseline of 4 for not introducing confusion or redundancy.
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 clearly states the verb 'Get' and the resource 'information about available courts and their document counts', which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'search_case_law', which might also involve court information but with different functionality.
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?
The description provides no guidance on when to use this tool versus alternatives like 'search_case_law'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search for Swiss court decisions using Entscheidsuche database
| Name | Required | Description | Default |
|---|---|---|---|
| from | No | Starting position for pagination | |
| query | Yes | Search query for legal cases | |
| size | No | Number of results to return (max 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic function. It lacks details on behavioral traits such as rate limits, authentication needs, error handling, or what the search returns (e.g., result format, metadata). This is inadequate for a search tool with no output schema.
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 description is a single, efficient sentence that directly states the tool's purpose without redundancy. It's front-loaded and wastes no words, making it easy to parse quickly.
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?
Given the complexity of a search tool with no annotations or output schema, the description is insufficient. It doesn't explain what the search returns, how results are structured, or any limitations, leaving gaps for the agent to understand the tool's behavior fully.
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?
Schema description coverage is 100%, so the schema fully documents parameters like 'query' for search terms and 'from/size' for pagination. The description adds no additional meaning beyond implying a legal context, meeting the baseline for high schema coverage.
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 clearly states the action ('Search') and target resource ('Swiss court decisions') with the specific database ('Entscheidsuche'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_document' or 'list_courts', which might also retrieve legal information.
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?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention scenarios for searching case law compared to getting specific documents or listing courts, leaving the agent to infer usage from tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0get_documentlist_courtssearch_case_lawEach tool has a clearly distinct purpose: get_document retrieves specific document content, list_courts provides metadata about courts, and search_case_law performs searches across the database. There is no overlap in functionality, making tool selection straightforward for an agent.
All tool names follow a consistent verb_noun pattern (get_document, list_courts, search_case_law) with clear, descriptive verbs. There are no deviations in naming conventions, making the set predictable and easy to understand.
With only 3 tools, the server feels somewhat thin for a legal document search domain. While the tools cover core operations (retrieve, list, search), more comprehensive coverage might include tools for filtering, advanced search, or document metadata management, suggesting a borderline appropriateness.
The tools provide basic CRUD-like operations (get, list, search) for legal documents and courts, but there are notable gaps. For example, there is no tool for updating or deleting documents, managing user queries, or handling advanced search parameters, which could limit agent effectiveness in complex workflows.
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