
Dactic MCP server
Which MCP servers are Dactic's own, from the official registry and from asking its own domain, whether they answer, and what they offer. A program checked each of these, nobody copied them from a product page.
read 2026-11-04
- Registry nameio.dactic/dactic-mcpverified in the MCP registry
The registry name sits under dactic.io. The registry only lets a publisher use that namespace after proving control of the domain through DNS or HTTP.
- Stateanswerschecked 2026-11-04
- Tools34
- Server calls itselfdactic-mcp
- Server version0.7.0
- Protocol version2025-06-18
On 2026-11-04 the server answered initialize and tools/list without a sign-in. First answer in 221 ms.
- Whether its tools do the product's job has not been judged yet.
- Checked on 1 of the 7 days it takes to judge reliability.
Once connected
- create_agent_from_process change data without a sign-in: anyone with the address can call them.
- Parameters are untyped or undescribed in 33 of 34 tools: check arguments before calling.
Said by rules from the measurements above. The likely first call is a model's pick from the tool list; read its description before relying on it.
- INITE MCP scoreafter a weeka score needs 7 daily checks: 1 so far
- Answeredmeasuring1 of the 7 daily checks it takes to print a share
- Median first answer232 ms
- Space in an agent's context≈ 5,885 tokensthe definitions of all its tools (34), which an agent carries on every turn
- Tool definitionsB · 84 of 100
- Typed results34 of 34 toolsdeclared outputSchema: results come typed, read once
- Parameters without a description: in 33 of 34
Worth a look
- Tools that change data, on a server that answers without a sign-in: create_agent_from_process
A program checks the server once a day: initialize and tools/list, no model. Tokens are the definitions' length at about four characters a token. The grade averages six checks of every tool's name, description, schema and annotations; it says how well the tools are described, not whether they work. The score weighs what was measured and nothing else: answering (25%), doing the product's job (25%), definitions (20%), context (10%), use (10%) and how readily a client connects (10%). A part that was not measured is left out, and a hidden instruction caps the score at 40. The state of vendors' MCP servers: method and numbers →
list_agentsList 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_agentGet 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_agentLoad 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…
invoke_agentRun 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…
resolve_termsLook 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_freshnessIs my Dactic knowledge up to date? Reports each surface (app sync, confirmed knowledge, terminology, approved playbook, department policies, skills, and optionally one agent) as fresh, stale, empty or unknown, with a recommendation for…
get_policyGet 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…
list_skillsList 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_skillGet one of your Dactic skills by id, with its full procedure at disclosure_tier L3.
ask_knowledgeAnswer 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…
get_context_bundleGet 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 confirmed…
get_user_contextYour own Dactic profile for personalising answers: job title, team, department and role; work context (role, guardrails, preferences); confirmed knowledge (paginated; unconfirmed files are counted, not shown); connected apps; tools you…
get_knowledge_provenanceWhere 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…
submit_agent_feedbackFile 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…
check_against_policyAdvisory 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…
get_skill_usageHow 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…
synthesize_agentDraft 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…
create_agent_from_processDraft 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). Before calling, ask the…
get_task_statusStatus 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.
searchSearch your Dactic knowledge (your skills, agents and approved 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.
fetchFetch the full text of one Dactic item by the id search returned, with a link to it.
get_usageYour Dactic AI usage (tokens by operation) over the last N days; scope=org is for org admins.
get_sync_statusReport recorded sync progress, last successful sync, approved source coverage and safe recovery guidance. Credential linkage is not proof of current access.
get_feedback_statusFollow the recorded processing/application state of your submitted agent feedback. No immediate agent change is implied.
recommend_agentMatch 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_versionsCompare 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_gapsAssess task preparation using available knowledge, skills, policies, terminology and sync readiness. Returns blocking/nonblocking gaps; unknown requirements or execution permissions remain unknown.
get_entity_contextFollow 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_deltaRetrieve 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…
retrieve_similar_casesFind 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_datasetQuery the approved synced Monday item view with supported scalar filters, sorting, grouping and count/sum aggregation. Fields are base identifiers or column:<stored-column-id>. Returns typed rows, pagination and explicit sync/coverage…
guide_workflowBuild 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…
recommend_new_agentsAfter 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…
deploy_agentFirst 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…
How to connect
Add the server to your MCP client config. Claude Desktop, Cursor and most other clients read this shape:
{
"mcpServers": {
"dactic-mcp": {
"type": "http",
"url": "https://mcp.app.dactic.io/mcp"
}
}
}Add it
Claude Code, in a terminal
claude mcp add --transport http dactic https://mcp.app.dactic.io/mcpclaude.ai, ChatGPT and other clients: add https://mcp.app.dactic.io/mcp as a custom connector in the settings.
Each line is something a program found when it went looking: the registry entry, the server's own answer, a spec that parses. A missing line means we did not find it, not that it does not exist.
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