grok-mcp
grok-mcp
xAI Grok API를 래핑하는 MCP 서버입니다. Claude 및 기타 AI 에이전트가 사고, 계획 및 실시간 검색을 Grok에 위임할 수 있도록 합니다.
빠른 시작
모든 기기에서 Claude Code에 추가하는 한 줄 명령어:
claude mcp add grok -e XAI_API_KEY=your-key -- npx -y @pkwadsy/grok-mcpconsole.x.ai에서 xAI API 키가 필요합니다.
대안: 프로젝트 구성
프로젝트의 .mcp.json에 추가:
{
"mcpServers": {
"grok": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@pkwadsy/grok-mcp"],
"env": {
"XAI_API_KEY": "your-xai-api-key"
}
}
}
}Related MCP server: grok-search-mcp
도구
ask_grok
선택적 파일 컨텍스트, 웹 검색 및 X/Twitter 검색을 사용하여 Grok에게 질문합니다.
매개변수 | 유형 | 필수 | 설명 |
| string | 예 | Grok을 위한 질문 또는 작업 |
| string[] | 아니요 | 컨텍스트에 포함할 파일 (아래 파일 구문 참조) |
| number | 아니요 | 최대 파일 수 재정의 (기본값 50) |
| number | 아니요 | 파일당 최대 크기(KB) 재정의 (기본값 32) |
| string | 아니요 | 사용자 지정 시스템 프롬프트 |
| string | 아니요 | 사용할 모델 (기본값: |
| boolean | 아니요 | 웹 검색, 기본적으로 활성화됨 |
| boolean | 아니요 | X/Twitter 검색 활성화 |
check_files
파일 확인을 위한 드라이 런(Dry-run)입니다. Grok을 호출하지 않고 모든 파일의 유효성을 검사하고 크기를 표시합니다. check_files가 통과하면 ask_grok도 통과합니다.
매개변수 | 유형 | 필수 | 설명 |
| string[] | 예 | 확인할 파일 ( |
| number | 아니요 | 최대 파일 수 재정의 (기본값 50) |
| number | 아니요 | 파일당 최대 크기(KB) 재정의 (기본값 32) |
파일 구문
파일은 다음과 같은 간결한 구문을 사용하여 문자열 배열로 전달됩니다:
구문 | 설명 |
| 전체 파일 |
| 10~30행 |
| 10행만 |
| Glob 패턴 |
| 파일당 크기 제한 우회 |
| 행 범위와 강제 적용 결합 |
안전 제한
제한 | 기본값 | 재정의 |
호출당 파일 수 | 50 |
|
파일당 크기 | 32 KB |
|
총 컨텍스트 | 256 KB | 하드 캡, 재정의 불가 |
사용 가능한 모델
grok-4.20-multi-agent— 멀티 에이전트 모드, 아키텍처 및 계획에 적합 (기본값)grok-4.20-reasoning— 플래그십 추론 모델grok-4.20-non-reasoning— 빠름, 추론 없음grok-4.1-fast-reasoning— 더 저렴한 추론 모델grok-4.1-fast-non-reasoning— 가장 저렴하고 빠름
예시
파일 컨텍스트와 함께 질문:
prompt: "Review this code for bugs"
files: ["src/index.ts", "src/utils.ts:20-50"]웹 검색:
prompt: "What happened in tech news today?"X/Twitter 검색:
prompt: "What are people saying about the new React release?"
x_search: true질문 전 파일 확인:
files: ["src/**/*.ts"]라이선스
MIT
Available Tools
2 toolsask_grokA
Ask Grok a question. Grok is great for thinking, planning, architecture, and real-time search via web and X/Twitter. Use web_search for current information from the internet. Use x_search to find and analyze posts on X/Twitter. IMPORTANT: Grok has no context about your conversation or codebase. Always include all relevant context directly in the prompt — file contents, error messages, architecture details, constraints, and goals. The more context you provide, the better Grok's response will be. Do not assume Grok knows anything about the current project. Use the files parameter to automatically include file contents with line numbers — this is preferred over pasting code into the prompt. File paths are resolved relative to the server working directory: /app. Responses include a response_id — pass it back as previous_response_id to continue a conversation without resending context.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The question or task for Grok. Include all relevant context — constraints, background, and goals — since Grok has no access to your conversation or files. Use the files parameter to attach source code rather than pasting it inline | |
| previous_response_id | No | Response ID from a previous ask_grok call. Continues the conversation — Grok remembers all prior context so you don't need to resend files or repeat background. Not supported by multi-agent model (beta limitation) | |
| files | No | Files to include in context. Compact syntax: "path/to/file" (whole file), "path/to/file:10-30" (lines 10-30), "path/to/file:10" (just line 10), "src/**/*.ts" (glob pattern), "large-file.ts:force" (bypass per-file size limit). Paths resolve relative to server cwd. | |
| max_files | No | Override max file count (default 50). Useful when a glob legitimately matches many files | |
| max_file_size | No | Override max per-file size in KB (default 32). Applies to all files without :force suffix | |
| system_prompt | No | Custom system prompt to guide Grok's behavior | |
| model | No | Model to use. Defaults to grok-4.20-multi-agent. Options: grok-4.20-multi-agent, grok-4.20-reasoning, grok-4.20-non-reasoning, grok-4.1-fast-reasoning, grok-4.1-fast-non-reasoning | |
| web_search | No | Web search is enabled by default. Set to false to disable | |
| x_search | No | Enable X/Twitter search to find and analyze posts |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses behavioral traits: Grok has no context about conversation or codebase, responses include a response_id for continuation, file inclusion syntax, model options, and search defaults. The limitation of previous_response_id in multi-agent mode is also noted.
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 fairly long but well-organized, using bold for emphasis and clear sections. Every sentence contributes essential information. Could be slightly more concise, but overall efficient for the complexity covered.
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 9 parameters and no output schema, the description is comprehensive: covers all input aspects, explains the output (response_id), gives continuation guidance, and addresses the critical context limitation. Complete and actionable.
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%, but the description adds substantial value: explains the rationale for using files, provides detailed file path syntax, clarifies the purpose of previous_response_id, and describes model options and search behavior. It enriches the parameter meanings significantly 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 'Ask Grok a question' and outlines what Grok excels at (thinking, planning, architecture, real-time search). It distinguishes from related tools like web_search and x_search, though they are not listed as siblings on this server. The purpose is specific and unambiguous.
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?
Explicitly provides when to use this tool vs alternatives: 'Use web_search for current information... Use x_search to find and analyze posts.' Also gives critical usage guidance: include full context, use files parameter, how to continue conversations with previous_response_id. No ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_filesA
Dry-run file resolution. Use this before ask_grok to verify files will resolve correctly and check context size. Uses the same validation as ask_grok — if check_files passes, ask_grok will too. File paths resolve relative to: /app
| Name | Required | Description | Default |
|---|---|---|---|
| files | Yes | Files to check. Same syntax as ask_grok: "path/to/file", "path/to/file:10-30", "src/**/*.ts", "large-file.ts:force" | |
| max_files | No | Override max file count (default 50) | |
| max_file_size | No | Override max per-file size in KB (default 32) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the tool is a dry-run (non-destructive), verifies file resolution, checks context size, and states that file paths resolve relative to /app. It doesn't detail error behavior or rate limits, but for a simple check tool this is adequate.
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 three sentences, with the primary purpose front-loaded. Every sentence adds essential information without 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 the tool's simplicity, no output schema, and a single sibling, the description covers the core functionality and relationship well. It explains validation equivalence and file resolution. It does not describe the return format, but the overall completeness is sufficient for an agent to use the tool correctly.
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 100% coverage with detailed descriptions for all three parameters. The description adds an important context note about file paths resolving relative to /app, which is not in the schema. However, this is environmental context rather than parameter semantics, so the baseline 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 performs a 'dry-run file resolution' and explicitly differentiates it from its sibling 'ask_grok' by positioning it as a preparatory verification step. The verb 'check' and noun 'files' are specific.
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 explicit usage guidance: 'Use this before ask_grok' and explains that if check_files passes, ask_grok will too. It also notes the same validation logic, giving clear context for when to use this tool versus the alternative.
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.
2 tool updates
v1.4.0- First observed
ask_grok - First observed
check_files
TDQS
Scored across 2 tools
ask_grok and check_files serve clearly distinct purposes: one is for querying Grok, the other is a dry-run validator for file resolution. No overlap or ambiguity.
Both tool names follow a consistent verb_noun pattern (ask_grok, check_files), using underscores and clear verbs.
Only 2 tools feels thin for a server that provides access to Grok, which could benefit from additional tools for conversation management or specialized searches.
The tool set lacks basic conversational features like retrieving history or managing context, and the promised web_search/x_search capabilities are not exposed as separate tools, limiting functionality.
Maintenance
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