Dactic

Was du damit machen kannst

Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.

• Verbindung: Läuft in der Cloud
• Transport: Streamable HTTP
• Kategorie: Sonstiges

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

Du brauchst

• Läuft in der CloudNichts zu installieren; die Verbindung läuft übers Internet

Welche App nutzt du?

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

Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.

Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 6. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

• 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

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026

• ✓ Bestanden

  Entwickler passt zum Repo

  Der Registry-Name wurde über die Domain dactic.io bestätigt (die Registry prüft, wem die Domain gehört)

• … Noch nicht geprüft

  Wird noch gepflegt

  Dieses Repo haben wir noch nicht von GitHub gelesen

• … Noch nicht geprüft

  Hat eine Lizenz

  Dieses Repo haben wir noch nicht von GitHub gelesen

• ✓ Bestanden

  Endpunkt antwortet

  Antwort in 425 ms (HTTP 200)

• – Nicht zutreffend

  Anmeldung mit OAuth

  Keine Anmeldung nötig

• ✓ Bestanden

  Keine versteckten Anweisungen in Tool-Beschreibungen

  Wir haben 34 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Im Vergleich mit anderen in Sonstigesi

• Mehr Sterne als 0 % der anderen 32403 Server in dieser Kategorie
• Neuer in der Registry veröffentlicht als 94 % der anderen 32403 Server in dieser Kategorie
• Basischecks gleich gut wie oder besser als bei 100 % der anderen 32403 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Alternativen

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

README vom Entwickler

{"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 .