Integrations·AI & ML
Modelry + OpenClaw
Give your autonomous agents a live connection to Modelry: managed, secure, and ready in minutes.
Modelry is a platform for building, deploying, and managing machine learning models. On Molted, your OpenClaw agents connect to Modelry through the managed MCP integration layer, with no glue code, no servers to run, and no credentials baked into containers. The agent can call models, run inference, and chain AI capabilities for Modelry, autonomously and within the guardrails you set.
Available actions
15 ready-to-use Modelry actions.
Your OpenClaw agents can call any of these Modelry actions directly through Molted's managed MCP layer. No wrappers, no boilerplate.
MODELRY_CREATE_WORKSPACE
Create Workspace
Tool to create a new workspace. use when you need to group products and embeds into a dedicated workspace. call after authenticating and specifying workspace…
MODELRY_DELETE_EMBED
Delete Modelry Embed
Tool to delete an embed. tries multiple common endpoint patterns and treats 404 as idempotent success after exhausting candidates (embed already deleted or not…
MODELRY_DELETE_PRODUCT
Delete Modelry Product
Tool to delete a product. use after confirming the product id.
MODELRY_DELETE_PRODUCT_REPOSITORY
Delete Product Repository
Tool to delete a product repository. use after confirming the repository id.
MODELRY_DELETE_WORKSPACE
Delete Modelry Workspace
Tool to delete a workspace. use after confirming the workspace id.
MODELRY_GET_EMBED
Get Embed
Tool to retrieve details of a specific embed. use after confirming the embed id.
MODELRY_GET_PRODUCT_REPOSITORY
Get Product Repository
Tool to retrieve details of a specific product repository. use when you have a repository id and need its details.
MODELRY_GET_WORKSPACE
Get Workspace
Tool to retrieve details for a specific workspace. use after confirming the workspace id.
MODELRY_LIST_EMBEDS
List Embeds
Tool to list available embeds. use when you need embed ids for downstream actions (e.g., modelry get embed). supports optional pagination.
MODELRY_LIST_MODELING_REQUESTS
List Modeling Requests
Tool to list all 3d modeling requests associated with the authenticated user's workspace. use after authenticating to fetch your modeling requests.
+ 5 more Modelry actions, all callable by your agents.
How the connection works
Connect once. The agent acts.
Modelry connects with an API key you provide once; it is encrypted at rest and never shipped inside the agent's pod. Everything runs through Molted's managed MCP layer, so there is no integration code to write and nothing to keep running.
01
The agent requests access
Your OpenClaw agent asks for Modelry when a task needs it.
02
You approve the connection
Authorize Modelry once (API key). Credentials are encrypted at rest and scoped to what you allow.
03
The agent acts
It reads and writes to Modelry autonomously, inside your guardrails, with full audit and revocable access.
FAQ
Modelry on Molted, answered.
Q.01
Can OpenClaw agents use Modelry on Molted?
Yes. Modelry is one of 1,000+ apps available through Molted's managed MCP integration layer. Your agent requests access, you approve the connection, and it can act on Modelry straight away, with no integration code to write or maintain.
Q.02
How do I connect Modelry to my agent?
Modelry connects with an API key you provide once; it is encrypted at rest and never shipped inside the agent's pod.
Q.03
What can an agent actually do with Modelry?
Within the permissions you grant, an agent can call models, run inference, and chain AI capabilities. With Modelry, your agent can call models for generation, classification or extraction inside a workflow.
Q.04
Is my Modelry data and credentials secure?
Yes. Molted never bakes credentials into the agent's pod: every connection is brokered through the managed integration layer, secrets are encrypted at rest, and access stays scoped to what you approve. You can revoke Modelry access at any time.
Q.05
Do I have to run any infrastructure to use Modelry?
No. Molted is the managed operating environment for autonomous agents: compute, the MCP layer, browser automation and self-healing are all handled for you. Connecting Modelry is a configuration step, not an engineering project.
Q.06
Can several agents share one Modelry connection?
Each instance gets its own isolated, scoped Modelry connection by default, so agents stay separated. You decide which agents may reach Modelry and with which permissions.
Ship agents that use Modelry, not infrastructure.
Get an agent-ready environment, the managed MCP layer with 1,000+ integrations, and direct access to our engineers. Onboarding within days.