Dactic

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: 기타

설치

쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.

필요한 것

• 클라우드에서 실행설치할 것 없음. 인터넷으로 연결돼요

어떤 앱을 쓰세요?

https://mcp.app.dactic.io/mcp

claude mcp add --transport http dactic https://mcp.app.dactic.io/mcp

{
  "mcpServers": {
    "dactic": {
      "url": "https://mcp.app.dactic.io/mcp"
    }
  }
}

{
  "servers": {
    "dactic": {
      "type": "http",
      "url": "https://mcp.app.dactic.io/mcp"
    }
  }
}

https://mcp.app.dactic.io/mcp

선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.

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

할 수 있는 일

도구 이름과 설명은 서버가 2026년 11월 6일에 알려 준 그대로예요. 우리가 아니라 제작자가 쓴 글이고, 일반 텍스트로만 보여 드려요.

• list_agents

  List the Dactic agents you (the signed-in user) have deployed, newest first. Returns each agent's id, name, platform and status. Use load_agent to run one or get_agent for its details. Returns not_found when you have none.

• get_agent

  Get one of your Dactic agents by id: its name, platform, status, complete instructions and every skill (name, description, full procedure). Never returns another user's agent.

• load_agent

  Load one of your Dactic agents (by agent_id or exact agent_name) so you can run it in this chat: returns its complete instructions and skills. Follow them exactly. Returns not_ready when the agent has no approved instructions, and not_found when no agent matches; it never returns

• invoke_agent

  Run one of your deployed Dactic agents. Claude agents start a Managed Agent session; Monday agents are run by Monday's own board automation. The response always includes the agent's complete instructions and skills. Retrying the same request returns the same run instead of starti

• resolve_terms

  Look up what company-specific terms mean, from your organization's confirmed Dactic terminology only. Terms that aren't confirmed come back in gaps; never guess their meaning.

• check_freshness

  Is my Dactic knowledge up to date? Reports each surface (app sync, knowledge, terminology, playbook, department policies, skills, and optionally one agent) as fresh, stale, empty or unknown, with a recommendation for anything not fresh. Pass refs from other Dactic tools to check

• get_policy

  Get your department's current policies with their source document. With query: the policies that apply to it (all of them when your department has few, else the closest matches; coverage says which). Returns not_found when none are published.

• list_skills

  List your active Dactic skills (procedures derived from your interviews). disclosure_tier L1 returns a catalog; L2/L3 add the procedure. Use get_skill for one skill. Returns not_found when you have none.

• get_skill

  Get one of your Dactic skills by id, with its full procedure at disclosure_tier L3.

• ask_knowledge

  Answer a question from your own Dactic context: matches holds evidence from your synced work data and current department policies related to the question; your_profile holds your work context, skills, agents and connected apps. When nothing matches, say so; never another user's d

• get_context_bundle

  Get everything a task needs from Dactic in one call; use it before doing a task, especially when running an agent. With agent_id: that agent's complete instructions and skills. Without: your most relevant skills. Plus your knowledge (confirmed first, then inferred from approved s

• get_user_context

  Your own Dactic profile for personalising answers: job title, team, department and role; work context (role, guardrails, preferences); knowledge files (paginated, confirmed first; each says confirmed or inferred); connected apps; tools you use. Only ever your own data, even for o

• get_knowledge_provenance

  Where did that come from? For refs returned by other Dactic tools (1-20), describes each item's source and a confidence of high, medium or low from a fixed rubric, with the rule that applied in `basis`. Rubric — terminology: high when confirmed with score >= 0.9 and no conflict,

• submit_agent_feedback

  File feedback about one of your own Dactic agents (e.g. 'it keeps CC'ing finance'). Quote the user's words in detail. First call without confirmation_code: you get a preview and a confirmation_code and nothing is saved; show the preview, ask the user to confirm, then call again w

• check_against_policy

  Advisory check of a draft reply, plan or action against your department's Dactic policies. Returns findings that quote the policy and the draft verbatim, with a suggested change, and says how many policies were checked. Present the result as advice: it is never a compliance sign-

• get_skill_usage

  How often your Dactic skills were listed and loaded by AI clients (ChatGPT, Claude…) over the last 7, 30 or 90 days, how many live agents use each, and a suggestion (promote, keep, review or trim) with its basis. Suggestions are advice and never change anything. data_since is whe

• synthesize_agent

  Draft a new Dactic agent for a task the user describes, built only from the user's own Dactic skills, policies and work context. Runs in the background: it returns a task_id at once; call get_task_status with it until the status is succeeded or failed. The result is a draft saved

• create_agent_from_process

  Draft a new Dactic agent, and the new skills it needs, from a process the user describes in this chat — use this when the user's existing skills don't cover the work (synthesize_agent only reuses existing skills). The input includes purpose, concrete ordered steps, trigger, resou

• get_task_status

  Status of a background task you started (e.g. synthesize_agent): queued, running, succeeded (with its result) or failed (with error_message). Only your own tasks; anything else is not_found.

• search

  Search your Dactic knowledge (your skills, agents and playbooks, and your organization's confirmed terminology, plus current department policies). Returns results with an id, title and link; call fetch with an id for the full text.

• fetch

  Fetch the full text of one Dactic item by the id search returned, with a link to it.

• get_usage

  Your Dactic AI usage (tokens by operation) over the last N days; scope=org is for org admins.

• get_sync_status

  Report recorded sync progress, last successful sync, approved source coverage and safe recovery guidance. Credential linkage is not proof of current access.

• get_feedback_status

  Follow the recorded processing/application state of your submitted agent feedback. No immediate agent change is implied.

• recommend_agent

  Match a task to accessible deployed agents by their stored instructions and skills. Returns candidate evidence and limitations; never runs or creates an agent.

• compare_agent_versions

  Compare two stored artifact versions of the same accessible agent/platform, with instruction diffs and skill additions/removals. Missing guardrails/parameters remain unknown. Never rolls back or deploys.

• find_context_gaps

  Assess task preparation using available knowledge, skills, policies, terminology and sync readiness. Returns blocking/nonblocking gaps; unknown requirements or execution permissions remain unknown.

• get_entity_context

  Follow bounded explicit stored links from an approved board, accessible agent/project or confirmed term. Returns entities, relationship bases, citations and missing-link gaps. Text similarity never establishes a dependency.

• get_context_delta

  Retrieve added/updated/removed permitted knowledge and published policies since an actor-bound snapshot cursor. Omit cursor for a complete bounded baseline. Expired cursors or changed scopes/permissions require a fresh baseline. Returns snapshot differences, not every intermediat

• retrieve_similar_cases

  Find comparable recent runs or resolved feedback owned by you. Returns recorded summaries/outcomes, citations and uncertainty; missing actions/outcomes remain unknown. Past outcomes do not guarantee success.

• query_work_dataset

  Query the approved synced Monday item view with supported scalar filters, sorting, grouping and count/sum aggregation. Fields are base identifiers or column: . Returns typed rows, pagination and explicit sync/coverage limits. Older syncs may lack structured columns. Never accepts

• guide_workflow

  Build advisory human-reviewed workflow options using accessible agents, context gaps, connection/sync readiness and provisional platform capabilities. Separates source, execution-platform and host connectors. Returns next actions and conservative net human-hours estimates only fr

• recommend_new_agents

  After confirming the user's goal, save a new recommendation iteration containing validated Claude draft proposals from their own skills/context. Optional priorities produce up to three proposals. A proposal never copies an agent or draft the user already has: when their skills ar

• deploy_agent

  First deployment of your selected saved draft. Call without confirmation_code for a preview, show it to the user and obtain authorization, then repeat the same definition/target with the code. Checks skills, source approvals and existing deploy readiness/billing gates. Returns a

기본 점검i

누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검

• ✓ 통과

  제작자와 저장소 일치

  레지스트리 이름이 도메인 dactic.io 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

  425ms 만에 응답(HTTP 200)

• – 해당 없음

  OAuth로 로그인

  로그인 필요 없음

• ✓ 통과

  도구 설명에 숨겨진 지시 없음

  도구 설명 34개를 읽었고, AI에게 보내는 숨겨진 지시는 없었어요

기타 카테고리의 다른 서버와 비교i

• 이 카테고리의 다른 서버 32403개 중 0%보다 스타가 많아요
• 이 카테고리의 다른 서버 32403개 중 94%보다 최근에 레지스트리에 공개됐어요
• 기본 점검 결과가 이 카테고리의 다른 서버 32403개 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:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i

제작자의 README

{"mcpServers":{"dactic":{"url":"https://mcp.app.dactic.io/mcp"}}}

claude mcp add --transport http dactic https://mcp.app.dactic.io/mcp

npm ci

docker build -t dactic-mcp:local .