ellmos-clatcher-mcp
Officialellmos-clatcher-mcp
🇩🇪 독일어 버전
Claude Patcher -- AI 코딩 에이전트가 기본적으로 갖추지 못한 유틸리티 도구를 제공하여 기능을 확장하는 MCP 서버입니다. 파일 복구, 형식 변환, 중복 탐지, 일괄 작업 등을 수행합니다.
ellmos MCP 제품군의 일부입니다:
서버 | 초점 | npm |
파일 시스템 작업, 프로세스 관리, 대화형 세션 |
| |
코드 분석, AST 파싱, 임포트 관리 |
| |
ellmos-clatcher-mcp | 유틸리티 도구: 복구, 변환, 탐지, 일괄 작업 |
|
각 서버는 서로 다른 영역을 다룹니다. 워크플로우에 따라 하나, 둘 또는 세 가지 모두를 사용하세요.
도구
도구 | 설명 |
| 손상된 JSON 복구: 주석, 후행 쉼표, 작은따옴표, BOM/NUL 제거 |
| 인코딩 문제 수정: BOM 제거, 이중 인코딩된 UTF-8, cp1252 아티팩트 수정 |
| 이중 인코딩으로 인해 깨진 독일어 움라우트 수정 (예: |
| JSON, YAML, TOML, XML, CSV 및 INI 간 변환 |
| 콘텐츠 해시(SHA256)를 기준으로 중복 파일을 찾아 동일한 콘텐츠별로 그룹화 |
| 두 디렉토리를 비교하거나, 스냅샷을 찍어 다음 호출 시 차이점 확인 |
| 정규식 패턴을 사용하여 파일 이름 변경 (드라이 런 미리보기 포함) |
| ZIP 아카이브 생성, 추출 또는 목록 확인 |
| 파일 해시 계산 (SHA256, MD5, SHA1, SHA512) 및 선택적 검증 |
| BOM 제거, 후행 공백 제거, 줄 바꿈 수정, NUL 바이트 제거 |
| 코드 파일에서 이모지 문자 찾기 |
| 텍스트에 대해 정규식 패턴을 테스트하고 그룹과 함께 모든 일치 항목 표시 |
모든 파괴적인 도구는 기본적으로 **드라이 런 모드(dry-run mode)**로 작동하며, 변경 사항을 적용하려면 명시적으로 dry_run: false가 필요합니다.
Related MCP server: Code Buddy
설치
Claude Code CLI
claude mcp add ellmos-clatcher-mcp -- npx ellmos-clatcher-mcpnpm (전역)
npm install -g ellmos-clatcher-mcp
claude mcp add ellmos-clatcher-mcp -- ellmos-clatcher소스에서 설치
git clone https://github.com/ellmos-ai/ellmos-clatcher-mcp.git
cd ellmos-clatcher-mcp
npm install
npm run build
node dist/index.js테스트
npm test12개의 모든 도구를 다루는 122개의 테스트(vitest)가 포함되어 있습니다.
요구 사항
Node.js >= 18
라이선스
ellmos-ai 생태계
이 MCP 서버는 ellmos-ai 생태계의 일부입니다 — AI 인프라, MCP 서버 및 지능형 도구.
MCP 서버 제품군
서버 | 도구 | 초점 | npm |
43 | 파일 시스템, 프로세스 관리, 대화형 세션 |
| |
17 | 코드 분석, AST 파싱, 임포트 관리 |
| |
12 | 파일 복구, 형식 변환, 일괄 작업 |
| |
13 | AI 어시스턴트를 통한 n8n 워크플로우 관리 |
|
AI 인프라
프로젝트 | 설명 |
LLM을 위한 텍스트 기반 OS — 109개 이상의 핸들러, 373개 이상의 도구, 932개 이상의 기술 | |
자동 라우팅 및 예산 추적 기능을 갖춘 공급자 중립적 LLM 오케스트레이션 | |
경량 에이전트 메모리, 커넥터 및 자동화 인프라 | |
자체 호스팅 AI 연구 스택 (Ollama + n8n + Rinnsal + KnowledgeDigest) | |
Claude Code를 위한 자율 에이전트 체인 프레임워크 | |
미니멀리스트 데이터베이스 기반 LLM OS 프로토타입 (4개 함수, 1개 테이블) | |
LLM 운영 체제용 테스트 프레임워크 (7개 차원) |
데스크톱 소프트웨어
저희 파트너 조직인 **open-bricks**는 AI 네이티브 데스크톱 애플리케이션을 번들로 제공합니다. 이는 AI 시대를 위해 구축된 현대적인 오픈 소스 소프트웨어 제품군입니다. 카테고리에는 파일 관리, 문서 도구, 개발자 유틸리티 등이 포함됩니다.
Haftung / Liability (책임)
이 프로젝트는 독일 민법(BGB) 제516조 이하에 따른 무상 오픈 소스 기부입니다. 저자의 책임은 독일 민법 제521조에 따라 고의 및 중과실로 제한됩니다. 또한 GPL-3.0 / MIT / Apache-2.0 제15~16조(선택한 라이선스에 따라 다름)의 책임 면제 조항이 적용됩니다.
사용자의 책임하에 사용하십시오. 유지 관리 약속, 가용성 보장, 오류 없음 또는 특정 목적에 대한 적합성에 대한 보증은 없습니다.
This project is an unpaid open-source donation. Liability is limited to intent and gross negligence (§ 521 German Civil Code). Use at your own risk. No warranty, no maintenance guarantee, no fitness-for-purpose assumed.
Available Tools
12 toolsarchiveB
Create, extract, or list ZIP archives.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | Operation | |
| extract_to | No | Extraction directory (for extract) | |
| archive_path | Yes | Path to the ZIP file | |
| source_paths | No | Files/directories to add (for create) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It does not disclose side effects such as overwriting existing files during extraction, behavior for nested directories, or what happens if the archive already exists during creation.
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 sentence of 7 words with no superfluous information. Every word is necessary, making it highly concise.
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?
Without an output schema or annotations, the description lacks details on return values (e.g., for list action), error handling, and platform-specific behavior. This is insufficient for a multi-action file tool.
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 coverage is 100%, so the schema thoroughly documents each parameter. The description adds no new parameter details beyond what the schema's enum and descriptions provide, resulting in a baseline score.
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 'Create, extract, or list ZIP archives' clearly specifies the verb (create, extract, list) and the resource (ZIP archives). It effectively distinguishes this tool from siblings like batch_rename or checksum, which have different purposes.
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. There is no mention of prerequisites, typical use cases, or when to choose each action (create vs extract vs list).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
batch_renameA
Rename multiple files using regex pattern, prefix/suffix, or counter. Always preview first with dry_run=true.
| Name | Required | Description | Default |
|---|---|---|---|
| dry_run | No | true = preview only | |
| pattern | Yes | Regex pattern to match in filenames | |
| directory | Yes | Directory containing files to rename | |
| extensions | No | Comma-separated extensions to filter (e.g. 'jpg,png') | |
| replacement | Yes | Replacement string ($1, $2 for capture groups) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It mentions renaming and dry_run preview but does not detail actual effects when dry_run=false, permissions needed, or if original files are preserved. Partial transparency.
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 two sentences, front-loading the core purpose and key usage tip. No redundant information.
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?
The description does not explain return value (e.g., list of renamed files, errors). Without output schema, agents lack understanding of what to expect after execution.
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 covers 100% of parameters, but the description introduces 'prefix/suffix or counter' as methods not reflected in the schema. This mismatch could mislead an agent into expecting parameters that do not exist.
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 'Rename multiple files' using specific methods (regex, prefix/suffix, counter) and distinguishes this tool from sibling tools like archive or regex_test.
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 advises 'Always preview first with dry_run=true', providing clear usage guidance. It does not explicitly exclude scenarios or name alternatives, but the advice is direct and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
checksumA
Calculate file hash (SHA256, MD5, SHA1, SHA512). Optionally verify against expected hash.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| expected | No | Expected hash to verify against | |
| algorithm | No | sha256 |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses read-only behavior (calculate hash) and optional verification, but lacks details on side effects, permissions, or output format. No annotations exist to supplement.
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?
Single sentence front-loads 'Calculate file hash' and efficiently covers all aspects without 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?
Covers core functionality and algorithms, but lacks output format, error conditions, or behavior when verification fails. No output schema provided.
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?
Adds meaning beyond schema by mentioning optional verification against expected hash. Schema already covers path and algorithm enum, but description ties expected to verify action.
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?
Description clearly states the action (calculate file hash) and resource (file hash), with explicit algorithm options. It distinguishes from sibling tools like archive and batch_rename, which are unrelated.
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?
Description implies usage for hashing files and optional verification. While no explicit when-not or alternatives are provided, sibling tools are distinct, making context clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cleanup_fileC
Remove BOM, trailing whitespace, fix line endings, remove NUL bytes. Configurable per-option.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| dry_run | No | ||
| remove_bom | No | ||
| remove_nul_bytes | No | ||
| ensure_final_newline | No | ||
| normalize_line_endings | No | lf | |
| remove_trailing_whitespace | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose side effects and behavior. It states the tool modifies files but omits whether it edits in-place, creates backups, or its safety profile. The dry_run parameter hints at previewing, but this is not explained.
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 short (two sentences) and covers core functionality. While concise, it lacks structured organization and could benefit from bullet points or clearer separation of capabilities.
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 7 parameters and no output schema, the description is incomplete. It fails to mention return values, dry-run behavior, or default configurations. More context is needed for effective use.
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 only 14%. The description says 'Configurable per-option' but does not elaborate on individual parameters. Parameter names are somewhat self-explanatory, but enum and default values are not clarified.
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 lists specific cleanup operations (BOM, whitespace, line endings, NUL bytes) and states configurability. It clearly identifies the tool's function, though it could better differentiate from sibling tools like fix_encoding.
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 on when to use this tool versus alternatives. The description does not mention prerequisites, suitable contexts, or scenarios to avoid.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_formatA
Convert between data formats: JSON, YAML, TOML, XML, CSV, INI. Reads input file and writes output file.
| Name | Required | Description | Default |
|---|---|---|---|
| input_path | Yes | Source file path | |
| output_path | Yes | Target file path | |
| input_format | Yes | Source format | |
| output_format | Yes | Target format |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only states 'reads input file and writes output file', lacking details on error handling, overwrite behavior, validation, or limitations. For a conversion tool, more behavioral context is needed.
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 concise sentence that clearly states the tool's purpose and action. No unnecessary words, well-structured for quick parsing.
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 4 required parameters and no output schema or annotations, the description covers the core function but omits return value, error behavior, and potential constraints. Adequate but not thorough.
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 coverage is 100%, and the description does not add meaning beyond the schema. The schema already describes each parameter adequately. Baseline score of 3 is appropriate.
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 explicitly states the tool converts between data formats and lists supported formats (JSON, YAML, TOML, XML, CSV, INI). It clearly distinguishes from sibling tools like archive, batch_rename, etc., which serve different purposes.
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 implies usage for format conversion but provides no explicit when-to-use or when-not-to-use guidance. No alternatives are mentioned, though siblings are unrelated functions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_dupesB
Find duplicate files in a directory by content hash (SHA256). Groups files with identical content.
| Name | Required | Description | Default |
|---|---|---|---|
| min_size | No | Minimum file size in bytes (skip empty files) | |
| directory | Yes | Directory to scan | |
| recursive | No | Scan subdirectories | |
| extensions | No | Comma-separated file extensions to check (e.g. 'py,js,ts'). Empty = all files |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the hashing algorithm and grouping behavior, but lacks details on performance implications (e.g., scanning large directories), file permissions, or handling of symbolic links. Without annotations, more disclosure is needed.
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?
A single sentence that is concise and front-loaded, conveying the essential purpose and method without extraneous words.
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?
The description lacks information about the return format (e.g., list of file groups) and error handling. Given no output schema and no annotations, the description should provide more context about what the tool returns and its behavior.
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 coverage is 100% (all 4 parameters described). The description does not add parameter-specific details beyond the schema, but the schema itself is clear. Baseline score of 3 is appropriate.
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 tool finds duplicate files using SHA256 hashing and groups identical content. This distinguishes it from siblings like 'checksum' (computes hashes) and 'cleanup_file' (deletes files).
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 list of sibling tools is given but not referenced, and no context is provided about situations where this tool is appropriate or not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_encodingA
Fix encoding issues: detect and repair BOM, broken UTF-8, cp1252 artifacts. Common on Windows.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| dry_run | No | true = analyze only, false = write fixed file |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must reveal behavioral traits. It mentions 'detect and repair' but does not clarify default behavior (dry_run=true means analysis-only) or potential side effects like file modification. The schema supplies dry-run semantics, but the description adds no behavioral 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 at two sentences, delivering the core purpose and common context without wasted words. It is front-loaded with the main action.
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?
While the description explains what encoding issues it fixes and mentions Windows, it lacks information about return values, the analysis/repair process, and default behavior (dry_run). For a tool with no output schema, more detail on output or success indicators would improve completeness.
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 coverage is 100% with clear descriptions for both parameters (path and dry_run). The tool description does not add extra meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
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 tool's purpose: fixing encoding issues, specifically BOM, broken UTF-8, and cp1252 artifacts. It uses a specific verb ('fix') and resource ('encoding issues'), and distinguishes itself from siblings like 'fix_umlauts' by listing concrete problems.
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 implies usage when encoding problems are present, especially on Windows, but does not explicitly state when to use this tool over alternatives like 'fix_umlauts' or 'convert_format'. No exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_jsonA
Repair broken JSON: strip comments, fix trailing commas, convert single quotes, remove BOM/NUL. Supports dry_run mode.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the JSON file | |
| dry_run | No | true = analyze only, false = write repaired file |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description mentions dry_run mode behavior but does not disclose potential side effects like overwriting the original file or creating backups, which are important for a repair tool.
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, front-loaded sentence that efficiently conveys the tool's action and key features with no redundant information.
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 no output schema, the description omits what the tool returns (e.g., success status, repaired content), leaving an information gap for the agent about the tool's output.
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 coverage is 100%, and the description only repeats the dry_run behavior without adding extra meaning about path requirements or expected file format beyond the schema.
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 tool's purpose: 'Repair broken JSON' and lists specific fixes (strip comments, fix trailing commas, convert single quotes, remove BOM/NUL), making it distinct from sibling tools like fix_encoding or cleanup_file.
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 implies when to use (for JSON files with syntax issues) but does not provide explicit guidance on when not to use or mention alternatives among siblings like fix_encoding or convert_format.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fix_umlautsA
Fix broken German umlauts from double-encoding or cp1252 artifacts (ä→ä, ö→ö, etc.)
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to the file | |
| dry_run | No | true = analyze only |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose whether the tool modifies the file in-place, requires backup, or other behavioral traits. The dry_run parameter hints at analysis, but effects of actual fix are unclear.
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?
Single sentence efficiently conveys purpose and examples with no redundancy.
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 simple tool with two well-described params and no output schema, description covers essential purpose. Could mention return values or confirmation of changes, but adequate for straightforward task.
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 covers 100% of parameters with descriptions. The description adds clarifying examples for the fix operation, but does not add meaning beyond what schema already provides for each 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?
Description clearly states the tool fixes broken German umlauts from double-encoding or cp1252, with specific character examples (ä→ä, etc.). It distinguishes itself from sibling 'fix_encoding' by being specific to umlauts.
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 explicit guidance on when to use this tool vs alternatives like 'fix_encoding'. The context of German umlauts is implied, but no when-not-to-use or comparison provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
folder_diffA
Compare two directories, or take a snapshot and compare on next call. Shows new, modified, and deleted files.
| Name | Required | Description | Default |
|---|---|---|---|
| directory | Yes | Directory to compare/snapshot | |
| compare_to | No | Second directory to compare against. Omit for snapshot mode. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry burden. It discloses that it shows new/modified/deleted files and has snapshot mode, but does not explicitly state it is read-only or mention performance implications.
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?
Two concise sentences with no unnecessary words. Front-loaded purpose and key details.
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?
Adequately covers purpose and parameters, but missing return format details (no output schema). Fairly complete for a simple diff tool.
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 coverage is 100%, and description adds clarification on snapshot mode (omit compare_to). Provides context beyond schema, though somewhat redundant.
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?
Description clearly states the tool compares directories with two modes (direct comparison and snapshot), and lists what it shows (new, modified, deleted files). Differentiates from sibling tools like archive or batch_rename.
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?
Describes two usage modes: provide two directories for comparison or omit compare_to for snapshot. Implicitly guides when to use each mode, but lacks explicit alternatives or when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
regex_testA
Test a regex pattern against text. Shows all matches with groups and positions.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to test against | |
| flags | No | Regex flags (g, i, m, s, u) | g |
| pattern | Yes | Regex pattern |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description reveals that matches, groups, and positions are shown, but lacks details on edge cases, errors, or performance. Basic behavioral info is present but not comprehensive.
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?
One efficient sentence that conveys core functionality without wasted words.
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?
No output schema; description states outputs (matches with groups and positions) but not format or structure. Adequate for a simple tool, but could be more explicit about return value organization.
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 covers all parameters (100%). The description does not add new meaning to parameters beyond what's in schema; it only describes output behavior. Baseline score is appropriate.
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 tool tests a regex pattern against text and lists outputs (matches, groups, positions). It distinguishes from siblings like archive or batch_rename which have unrelated purposes.
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 does not provide guidance on when to use this tool vs. alternatives, nor does it mention when not to use it. Usage is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_emojiB
Scan code files for emoji characters. Useful for finding accidental emojis in source code.
| Name | Required | Description | Default |
|---|---|---|---|
| directory | Yes | Directory to scan | |
| recursive | No | ||
| extensions | No | Comma-separated file extensions | py,js,ts,json,md,txt,yaml,yml,toml |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not state that the tool is read-only, nor does it describe any side effects, permissions, or handling of binary files. The scanning nature is implied but not explicitly declared as non-destructive.
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 two sentences, front-loaded with the action, and contains no redundant or unnecessary words. It efficiently communicates the core purpose.
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?
The description lacks information about the tool's output format, which is critical since there is no output schema. It does not explain how the tool returns results (e.g., list of files, count) or handle edge cases. The behavioral transparency gap further reduces completeness.
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 67% schema description coverage, the description adds no extra meaning to the parameters beyond what the schema provides. It does not explain the 'recursive' parameter (which lacks a schema description) or give examples of valid inputs.
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 explicitly states 'Scan code files for emoji characters', which is a specific verb and resource. It clearly differentiates from sibling tools, none of which target emoji scanning. The added phrase 'Useful for finding accidental emojis in source code' reinforces the purpose.
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 implies when to use ('Useful for finding accidental emojis'), but does not provide explicit guidance on when not to use or alternatives. Sibling tools do not overlap, so no exclusion needed, but the guidance is minimal.
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. Dates show when Glama detected each change.
12 tool updates
v1.0.5- First observed
archive - First observed
batch_rename - First observed
checksum - First observed
cleanup_file - First observed
convert_format - First observed
detect_dupes - First observed
fix_encoding - First observed
fix_json - First observed
fix_umlauts - First observed
folder_diff - First observed
regex_test - First observed
scan_emoji
TDQS
Tools are mostly distinct, but cleanup_file, fix_encoding, and fix_json all deal with BOM/encoding issues, which could cause confusion. However, descriptions help differentiate.
Names follow a general verb_noun or noun_verb pattern, but inconsistencies exist: 'archive' and 'checksum' are just nouns, 'detect_dupes' uses informal abbreviation, and 'regex_test' has reverse order.
With 12 tools covering archiving, renaming, checksums, cleanup, format conversion, duplicate detection, encoding fixes, folder diff, regex testing, and emoji scanning, the count is well-scoped for a file utility server.
The tool set covers a wide range of file manipulation and encoding repair tasks. Minor gaps exist, such as lack of a general find/replace or file move/copy, but core workflows are well supported.
Maintenance
Related MCP Connectors
Augments MCP Server - A comprehensive framework documentation provider for Claude Code
Nifty's MCP server — exposes tasks, projects, messages, and files as tools for AI agents.
MCP server for progressive tool usage at any scale (see https://klavis.ai)
MCP server unifying ERPs, CRMs, APIs and knowledge base for Claude, ChatGPT and Gemini.
Related MCP Servers
- AlicenseAqualityDmaintenanceMCP server that gives Claude Desktop and other desktop MCP clients filesystem powers—read, write, edit, and manage files like AI coding assistants.17869MIT
- AlicenseCqualityDmaintenanceA comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.287MIT
- FlicenseAqualityDmaintenanceA general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.11-
- AlicenseAqualityAmaintenanceComprehensive MCP server for filesystem operations, process management, interactive sessions, and async file search. Includes utilities for JSON repair, encoding fixes, duplicate detection, OCR, ZIP archives, and Markdown export.6467164MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ellmos-ai/ellmos-clatcher-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server