io.github.zenml-io/mcp-zenml
OCI · DOCKER.IO/ZENMLDOCKER/MCP-ZENML:2.0.0
MCP server for discovering, reading, and changing ZenML resources with compact generic tools
Available components
Last scanned (20 hours ago)
Scores higher than 82% of OCI servers
Category CI/CD and DevOps
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security0
- No malware scan is available for this kind of package: the supply-chain vendors we use do not cover it. This is a permanent gap in our coverage, not a finding about the package.Unverified
- Known CVEs could not be checked: this artifact ships no SBOM or dependency manifest, so there is no dependency list to read.Unverified
- Install-script risk not yet assessed.Unverified
- Dependency health could not be checked: this artifact ships no SBOM or dependency manifest, so there is no dependency list to read.Unverified
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 24 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability84
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (good).Pass
- Tool/resource definitions use about 1697 tokens (~84/item across 20 items; 16 tools + 4 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management83
- Stability observed for 25 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- All 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.Pass
- An AI judge read all 18 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
- Supports UI / widget rendering.Pass
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 14 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 73 to 77. That category is still filling its 30-day observation window: 22 days of observed history at the previous scan, 23 at this one. The score rises as the window fills, whether or not the server changes.
- 13 Oct 26 0
- Provenance: unverified → fail ▼ security
- 12 Oct 26 +5
- License: unverified → pass ▲ functional
- Maintenance: unverified → pass ▲ functional
- Licence: MIT functional
- 10 Oct 26 −1
- Provenance: fail → unverified ▼ security
- Maintenance: pass → unverified ▼ functional
- License: pass → unverified ▼ functional
- Licence: MIT functional
- 4 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 40 to 43. That category is still filling its 30-day observation window: 12 days of observed history at the previous scan, 13 at this one. The score rises as the window fills, whether or not the server changes.
- 2 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.
- 29 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.
- 28 Sept 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 16 Oct 2026 · Analysed oci/docker.io/zenmldocker/mcp-zenml:2.0.0
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | oci |
| Reason | No attestation published |
Background: How many MCP packages publish verified provenance →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
diagnose_zenml_setup ~69
Diagnose ZenML MCP server setup (env vars, connectivity, auth, versions). Returns structured diagnostics about the server's configuration and connectivity. This tool works even when the ZenML SDK is not installed or environment variables are missing - use it to troubleshoot setup issues.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
get_active_project ~45
Get the currently active project. Projects are organizational containers for ZenML resources. Most SDK methods are project-scoped, and this tool returns the default project context.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
get_active_user ~15
Get the currently active user.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
get_deployment_logs ~160
Get logs for a specific deployment. Retrieves logs from the deployment's underlying infrastructure. This is useful for debugging deployment issues or monitoring deployment behavior. Note: Log availability depends on the deployer plugin being installed and the deployment infrastructure supporting log retrieval. Args: name_id_or_prefix: The name, ID or prefix of the deployment project: Optional project scope (defaults to active project) tail: Number of recent log lines to retrieve (default: 100, max recommended: 500) Returns: Dict with 'logs' (string) and metadata about truncation if applicable
| Name | Type | Req | Description |
|---|---|---|---|
| name_id_or_prefix | string | yes | – |
| project | – | – | – |
| tail | integer | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_step_code ~42
Get the code for a step. Args: step_run_id: The ID of the step to retrieve
| Name | Type | Req | Description |
|---|---|---|---|
| step_run_id | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
get_step_logs ~94
Get the logs for a specific step run. Args: step_run_id: The ID of the step run to get logs for. source: Optional log source. Defaults to ZenML's ordinary ``step`` source. logs_id: Optional exact log record ID. Cannot be combined with ``source``.
| Name | Type | Req | Description |
|---|---|---|---|
| logs_id | – | – | – |
| source | – | – | – |
| step_run_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
open_pipeline_run_dashboard ~63
Open an interactive dashboard of recent ZenML pipeline runs. The dashboard shows pipeline runs with status indicators, expandable step details, filtering, and drill-down into step logs — all in an interactive UI. The dashboard fetches its own data dynamically.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
open_run_activity_chart ~58
Open an interactive chart showing pipeline run activity over the last 30 days. Shows a bar chart with daily run counts, hover tooltips, and status breakdown (completed in green, failed in red, other in amber).
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
trigger_pipeline ~296
Trigger a pipeline to run from the server. Args: pipeline_name_or_id: Optional name or ID of the pipeline to trigger. A snapshot or template can be triggered without it. snapshot_name_or_id: The name or ID of a specific snapshot to run (preferred) stack_name_or_id: Optional stack override for the run template_id: Deprecated template-based trigger parameter. Use `snapshot_name_or_id` for new integrations. ZenML 0.96.4 still retains run-template CRUD APIs. Usage examples: * Run the latest runnable snapshot for a pipeline: ```python trigger_pipeline(pipeline_name_or_id=<NAME>) ``` * Run the latest runnable snapshot for a pipeline on a specific stack: ```python trigger_pipeline( pipeline_name_or_id=<NAME>, stack_name_or_id=<STACK_NAME_OR_ID> ) ``` * Run a specific snapshot (RECOMMENDED): ```python trigger_pipeline( snapshot_name_or_id=<SNAPSHOT_NAME_OR_ID> ) ``` * Run a specific template (DEPRECATED - use snapshot_name_or_id instead): ```python trigger_pipeline(template_id=<ID>) ```
| Name | Type | Req | Description |
|---|---|---|---|
| pipeline_name_or_id | – | – | – |
| snapshot_name_or_id | – | – | – |
| stack_name_or_id | – | – | – |
| template_id | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_action_resource ~105
Run one finite ZenML lifecycle or relation action. Inspect ``zenml_describe_resources(resource_type, "action")`` for the exact action names and payload schema. Every identifier must be an exact UUID. Actions may have effects outside the ZenML server and are never retried.
| Name | Type | Req | Description |
|---|---|---|---|
| action | string | yes | – |
| payload | – | – | – |
| project_id | – | – | – |
| resource_id | string | yes | – |
| resource_type | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_create_resource ~86
Create one allowlisted ZenML resource with a strict typed payload. Inspect ``zenml_describe_resources(resource_type, "create")`` first. Project-scoped creates require an exact project UUID and never change the client's active project.
| Name | Type | Req | Description |
|---|---|---|---|
| model_id | – | – | – |
| payload | – | – | – |
| project_id | – | – | – |
| resource_type | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_delete_resource ~66
Delete or archive one exact UUID using bounded destructive options.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact_id | – | – | – |
| component_type | – | – | – |
| model_id | – | – | – |
| payload | – | – | – |
| project_id | – | – | – |
| resource_id | string | yes | – |
| resource_type | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_describe_resources ~74
Discover supported generic ZenML resources or one operation schema. With no arguments this returns a short catalog. Pass a canonical singular resource type to inspect its operations, and add an operation name for its bounded input schema and a small example.
| Name | Type | Req | Description |
|---|---|---|---|
| operation | – | – | – |
| resource_type | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_get_resource ~99
Get one allowlisted ZenML resource by its identifier. Artifact versions, model versions, and run steps require their parent identifier. Stack components require their fixed component type.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact_id | – | – | – |
| component_type | – | – | – |
| hydrate | – | – | – |
| model_id | – | – | – |
| pipeline_run_id | – | – | – |
| project_id | – | – | – |
| resource_id | string | yes | – |
| resource_type | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_list_resources ~106
List one allowlisted ZenML resource type with validated filters. Use ``zenml_describe_resources(resource_type, "list")`` to discover the accepted filters. Page sizes are capped at 200. Project-scoped reads use ``project_id`` when supplied and otherwise report the active project used.
| Name | Type | Req | Description |
|---|---|---|---|
| filters | – | – | – |
| page | integer | – | – |
| project_id | – | – | – |
| resource_type | string | yes | – |
| size | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
zenml_update_resource ~67
Update one exact UUID through an allowlisted operation-specific payload.
| Name | Type | Req | Description |
|---|---|---|---|
| artifact_id | – | – | – |
| component_type | – | – | – |
| model_id | – | – | – |
| payload | – | – | – |
| project_id | – | – | – |
| resource_id | string | yes | – |
| resource_type | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the io.github.zenml-io/mcp-zenml server?
io.github.zenml-io/mcp-zenml runs locally as a container image, launched with docker run --rm -i -e ZENML_STORE_URL -e ZENML_STORE_API_KEY -e ZENML_MCP_PROFILE -e ZENML_MCP_WRITE_POLICY docker.io/zenmldocker/mcp-zenml:2.0.0. Ready-made configuration for Claude, Cursor, VS Code, Codex and 3 more is on this page, copied from each client's own documentation.
oci · docker.io/zenmldocker/mcp-zenml:2.0.0
claude mcp add zenml-io-mcp-zenml -- docker run --rm -i -e ZENML_STORE_URL -e ZENML_STORE_API_KEY -e ZENML_MCP_PROFILE -e ZENML_MCP_WRITE_POLICY docker.io/zenmldocker/mcp-zenml:2.0.0
This image reads ZENML_STORE_URL, ZENML_STORE_API_KEY, ZENML_MCP_PROFILE and ZENML_MCP_WRITE_POLICY. Set them in your client's env block for this server; docker run -e passes each one through to the container.
What is the io.github.zenml-io/mcp-zenml server?
io.github.zenml-io/mcp-zenml is listed in the public MCP registry as io.github.zenml-io/mcp-zenml. MCP server for discovering, reading, and changing ZenML resources with compact generic tools. This page covers its container image (docker.io/zenmldocker/mcp-zenml:2.0.0).
Is the io.github.zenml-io/mcp-zenml server safe to use?
io.github.zenml-io/mcp-zenml scores 51 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the io.github.zenml-io/mcp-zenml server expose?
io.github.zenml-io/mcp-zenml exposes 16 tools: diagnose_zenml_setup, get_step_logs, zenml_describe_resources, zenml_list_resources, zenml_get_resource, and 11 more. Their descriptions and schemas cost roughly 1,445 tokens of context every time the server is loaded.
Is the io.github.zenml-io/mcp-zenml server still maintained?
io.github.zenml-io/mcp-zenml is still listed as active in the MCP registry. We last reached this channel on 16 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the io.github.zenml-io/mcp-zenml server under?
io.github.zenml-io/mcp-zenml declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.