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EvidenceLens MCP

by returdex

EvidenceLens MCP

EvidenceLens MCP는 결정적(deterministic) 읽기 전용 증거 검토 계약을 위한 TypeScript Model Context Protocol 서버입니다. 단일 review_evidence 도구는 Phase 2 인라인 콘텐츠와, 명시적으로 구성된 경우 Phase 3 파일시스템 소스를 수용합니다. 텍스트, 표, PDF, 이미지, 스크린샷을 출처(provenance) 메타데이터로 정규화하면서 발견 사항(findings)은 비워 두고 제공자 호출을 하지 않습니다.

로컬 개발

npm install
npm run dev
npm test
npm run build

npm run dev는 src/server.ts에서 stdio를 통해 MCP 서버를 시작합니다. npm test는 전체 계약, 정규화기, 픽스처, 안전성, MCP 프로토콜 테스트 스위트를 실행합니다. npm run build는 서버를 타입 검사하고 컴파일합니다.

Related MCP server: Observability Agent MCP

MCP 계약

정확한 인라인/파일시스템 요청 계약, 루트 구성 문법, 바이트 제한, filesystem:// 출처, 정규화된 증거 메타데이터, 안정적인 오류, 읽기 전용/제공자 없음/발견 사항 없음 경계에 대해서는 docs/mcp-contract.md를 참조하세요.

플랫폼 참고 사항: 기본 파일시스템 리더는 Linux에서 디스크립터 기준 컴포넌트 탐색을 사용합니다. 이 프로젝트가 지원하는 Node openat/openat2 바인딩이 없는 macOS에서는 기본 고정(anchored) 파일시스템 읽기가 정화된 ACCESS_DENIED와 바이트 없이 실패 폐쇄(fail closed)되며, 경로명 대체는 없습니다. Phase 2 인라인 증거는 계속 지원되며, 임베딩 테스트는 이식 가능한 파일시스템 읽기 커버리지를 위해 검토된 안전한 파일시스템 어댑터를 주입할 수 있습니다.

선택적 파일시스템 루트

루트가 구성되지 않으면 파일시스템 접근이 비활성화되며, 서버는 현재 디렉터리, 홈 디렉터리, 저장소 또는 다른 광범위한 기본값으로 절대 대체하지 않습니다. 쉼표 또는 세미콜론으로 구분된 반복 id=absolute-path 항목으로 명시적 루트를 구성하세요:

EVIDENCELENS_ALLOWED_ROOTS='course=/absolute/path/course;examples=/absolute/path/examples' npm run dev

루트 ID는 [A-Za-z][A-Za-z0-9_-]{0,31}와 일치해야 합니다. 빈 항목, 중복 ID, 정규 경로 충돌, 읽을 수 없는 루트, 디렉터리가 아닌 항목, 상대 경로, 잘못된 형식의 항목은 안정적인 메시지 Invalid filesystem root configuration으로 실패하며, 경로는 절대 에코되지 않습니다.

Available Tools

1 tool
review_evidenceReview EvidenceC
Read-onlyIdempotent

Accept Phase 1 evidence review metadata and return a deterministic skeleton response.

ParametersJSON Schema
NameRequiredDescriptionDefault
limitsNo
evidenceNo
reviewIdYes
objectiveYes

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already document the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), and the description adds the behavioral fact that the response is deterministic and skeleton-shaped. However, it does not say what the skeleton response contains or how input is handled, leaving a partial transparency gap.

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?

One sentence with no filler; the core action and outcome are front-loaded. It is appropriately sized but terse to the point of vagueness, so not a full 5.

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

Completeness2/5

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

Given a nested input schema and no output schema, the description is too thin: it does not explain the return shape, what 'Phase 1' means, or what evidence metadata is expected. Annotations cover safety but not operational context needed to invoke correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description needed to compensate for parameter meaning, but it mentions no parameter names or semantics. The schema itself provides constraints and enums, but the tool description contributes nothing to clarify reviewId, objective, evidence, or limits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a concrete verb-resource pair ('Accept Phase 1 evidence review metadata') and names the outcome ('return a deterministic skeleton response'), so an agent can tell this is a submission/stub endpoint for the review workflow. However, 'skeleton response' is unexplained and there is no sibling differentiation, though no siblings are listed.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance about when to call this tool versus any alternative, no workflow conditions, and no preconditions or exclusions. The only hint is the phrase 'Phase 1,' which is not elaborated.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.1.2
    • First observedreview_evidence

TDQS

C2.3/5.0

Scored across 1 tool

Disambiguation1/5

There is only one tool, so there is no ambiguity between tools, but the single tool's purpose is vague and could overlap with future tools. Since there is no set to disambiguate, it scores minimal.

Naming Consistency1/5

With only one tool, naming consistency is trivial but the naming is not informative; 'review_evidence' is a generic name that doesn't indicate what it does with evidence. No pattern can be assessed.

Tool Count1/5

A single tool for a server called 'EvidenceLens MCP' that claims to 'review evidence' is too thin. The scope suggests a larger toolset for evidence review, but only one trivial tool is provided.

Completeness1/5

The tool description says 'Accept Phase 1 evidence review metadata and return a deterministic skeleton response.' This covers only a tiny fraction of what an evidence review workflow would need; there's no way to submit actual evidence, get details, update reviews, or handle later phases.

Maintenance

ActivityActive
ResponsivenessNo issues

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