MCP Analytics

할 수 있는 일

이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.

• 연결 방식: 클라우드에서 실행
• 전송 방식: Streamable HTTP
• 카테고리: 마케팅 및 소셜 미디어
• 입력해야 할 값: X-API-Key

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

필요한 것

• 클라우드에서 실행설치할 것 없음. 인터넷으로 연결돼요

어떤 앱을 쓰세요?

claude mcp add --transport http analytics https://api.mcpanalytics.ai/mcp/api-key --header 'X-API-Key: your-value'

{
  "mcpServers": {
    "analytics": {
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

{
  "servers": {
    "analytics": {
      "type": "http",
      "url": "https://api.mcpanalytics.ai/mcp/api-key",
      "headers": {
        "X-API-Key": "your-value"
      }
    }
  }
}

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

직접 입력할 값

• X-API-Key 비밀 필수 HTTP header
  Your MCP Analytics API key, from https://account.mcpanalytics.ai

이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.

할 수 있는 일

도구 이름과 설명은 서버가 2026년 11월 8일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.

• account_link

  Direct link to the right account page for anything not doable in chat: billing, browser upload, report management. Hand the user the link and guide them.

• about

  Platform documentation and info: how it works (Answer, Analytics, Custom Analytics), usage.

• agent_advisor

  AI help desk: which analysis fits your question, interpreting results, fixing errors. Multi-turn.

• datasets_upload

  Get your data in. Pass `data` as an array of row objects to create the dataset immediately and get a dataset_ref ready for path_resolver; omit it to get an upload link for a file only the user can reach. Add replace_ref (uuid://ID:KEY) with data to REFRESH an existing dataset in

• datasets_list

  List and search your uploaded datasets, with fuzzy matching on name, description, and tags. Returns each dataset's uuid:// reference (the `usage` field) for use as dataset_ref in path_resolver and path_tool_run. The id alone ('uuid://dsv2_...') also works for your own datasets an

• discover_tools

  Browse the analyses you can run: the ones you commissioned plus the platform Standard Library (prebuilt tools; each result tagged source:'own' or 'standard_library'). Plain-language match; no query lists everything, your own first. Nothing fits? Commission it with path_resolver.

• tools_schema

  Get an analysis's parameter schema. ALWAYS call before path_tool_run.

• review_estimate

  The estimate as you review it WITH the user: the question as understood, the estimated answer (sample, marked), every place and its question, the page link, a review checklist. Before path_bespoke.

• adjust_estimate

  Apply the user's layout wishes to the estimate's page through the layout agent; a new named arrangement, nothing overwritten, no number changes.

• find_precedent

  Before estimating: how did we answer this objective before, on this data or any data? Prior packages and library runs with their tools, mappings, bespoke module names, method and verdicts. Platform-wide, read-only.

• check_tool_fit

  Before naming a library tool: does it fit THIS dataset for THIS question? Column mapping, missing required inputs, method-fit verdict, the places it delivers. Read-only.

• package_status

  Read an analytics package back: status, every run under it, the report link once delivered.

• my_objects

  List and search the objects you own across every question: the curated charts, tables and figures of each delivered package, grouped by objective.

• build_status

  Check a commissioned build in-chat: stage progress, queue position, rejection reason if the data didn't match the objective, honest ETA, report link when delivered.

• ask_library

  Ask a question across all your delivered analyses: a synthesized answer with citations back to specific reports.

• reports_list

  Your report library: every analysis delivered, with status and links. Pass semantic_query to search report content in plain language.

• warehouse

  Query your org's data warehouse free: browse the catalog (tables with column roles + computed metrics), semantically find data, plain-language ask, or named templates. Requires warehouse enablement (business plans).

• schedules

  Standing re-runs of analyses you own: action='create' (weekly/monthly against a re-runnable data reference, connector:// or an https:// link; report emailed after each run), 'list', or 'cancel'.

• reports_view

  Get a shareable browser link for a report, viewable without authentication.

• report_cards

  Browse a delivered report's individual cards (charts, tables, insights) inline in chat.

• path_resolver

  Which path a question about data should take (reuse, rerun, answer, tool_run, estimate, bespoke, ask or none), with the reason, every path's score and time, and the ready input for the path it picks. Executes nothing and charges nothing.

• path_reuse

  Hand back the report already delivered for this question on this data. Time: as path_resolver quotes.

• path_rerun

  Run a delivered analysis again, on its own dataset or a new one: the same tools and mappings, no rebuild. package_id may also be the person's own report link (a /rpt/ link or its rpt_ token) or estimate id (est_); it reruns their newest delivered package for it. Time: as path_res

• path_answer

  A read of the data (a total, an average, a count, the top group), computed on every row, in this response. When the question is not a read it says so and names the next step. Time: as path_resolver quotes. No key yet? Call it with objective and data (a small table, up to 200 rows

• path_tool_run

  Run one or more tested library tools on this dataset, with charts and a written report. No custom build. Time: as path_resolver quotes.

• path_estimate

  A rough answer over a sample and the layout of the full report, for the person to confirm before anything is ordered. Time: as path_resolver quotes.

• path_bespoke

  Order a custom analysis built for this data from a confirmed estimate, optionally with library tools alongside. Needs the person's yes and an idempotency key; a retry returns the first order. Time: as path_resolver quotes.

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 8일 점검

• ✓ 통과

  제작자와 저장소 일치

  레지스트리 이름이 도메인 mcpanalytics.ai 기준으로 확인되었어요(레지스트리가 도메인 소유를 확인해요)

• … 아직 점검 안 함

  계속 관리되고 있음

  아직 GitHub에서 이 저장소를 읽어 오지 않았어요

• … 아직 점검 안 함

  라이선스 있음

  아직 GitHub에서 이 저장소를 읽어 오지 않았어요

• ✓ 통과

  엔드포인트 응답

  302ms 만에 응답(HTTP 200)

• – 해당 없음

  OAuth로 로그인

  로그인 필요 없음

• ✓ 통과

  도구 설명에 숨겨진 지시 없음

  도구 설명 27개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요

마케팅 및 소셜 미디어 카테고리의 다른 서버와 비교i

• 이 카테고리의 다른 서버 3609개 중 0%보다 스타가 많아요
• 이 카테고리의 다른 서버 3609개 중 55%보다 최근에 레지스트리에 공개됐어요
• 기본 점검 결과가 이 카테고리의 다른 서버 3609개 중 100%와 같거나 더 좋아요

레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.

대안

같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.

카드 보는 법:↓ 주간 다운로드i★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

제작자의 README

{

claude mcp add --transport http mcpanalytics https://api.mcpanalytics.ai/mcp/api-key --header "X-API-Key: mcp_your_key_here"

curl -X POST https://api.mcpanalytics.ai/mcp/api-key \