Integrations·AI & ML

Give your autonomous agents a live connection to Honeyhive: managed, secure, and ready in minutes.
Honeyhive is an AI observability and evaluation platform for analyzing LLM apps. On Molted, your OpenClaw agents connect to Honeyhive 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 Honeyhive, autonomously and within the guardrails you set.
Available actions
Your OpenClaw agents can call any of these Honeyhive actions directly through Molted's managed MCP layer. No wrappers, no boilerplate.
HONEYHIVE_ADD_DATAPOINTS_TO_DATASET
Tool to add datapoints to a dataset. Use when you need to append multiple entries with specified input, ground truth, and history mappings.
HONEYHIVE_CREATE_BATCH_MODEL_EVENTS
Tool to create multiple model events in a single request. Use when you need to log a batch of event interactions to HoneyHive.
HONEYHIVE_CREATE_BATCH_TOOL_EVENTS
Tool to log a batch of external API calls as tool events. Use when you need to record multiple tool events in one request—use after gathering all event data.
HONEYHIVE_CREATE_DATASET
Tool to create a dataset. Use when you need to initialize a new dataset within a project.
HONEYHIVE_CREATE_TOOL
Tool to create a new tool. Use when you need to register a new function or plugin for invocation.
HONEYHIVE_DELETE_DATAPOINT
Tool to delete a specific datapoint by its ID. Use when you need to remove a datapoint from HoneyHive after confirming its identifier.
HONEYHIVE_DELETE_DATASET
Tool to delete a dataset by ID. Use when you need to remove a dataset after confirming its ID.
HONEYHIVE_END_EVALUATION_RUN
Tool to mark an evaluation run as completed. Use after finishing manual evaluations to update the run status to completed.
HONEYHIVE_GET_CONFIGURATIONS
Tool to retrieve a list of configurations. Use when you need to fetch all configurations for a specific project before making changes.
HONEYHIVE_GET_DATASETS
Tool to retrieve a list of datasets. Use when you need to fetch datasets for a specific project with optional filters.
+ 14 more Honeyhive actions, all callable by your agents.
How the connection works
Honeyhive 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
Your OpenClaw agent asks for Honeyhive when a task needs it.
02
Authorize Honeyhive once (API key). Credentials are encrypted at rest and scoped to what you allow.
03
It reads and writes to Honeyhive autonomously, inside your guardrails, with full audit and revocable access.
FAQ
Q.01
Yes. Honeyhive 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 Honeyhive straight away, with no integration code to write or maintain.
Q.02
Honeyhive connects with an API key you provide once; it is encrypted at rest and never shipped inside the agent's pod.
Q.03
Within the permissions you grant, an agent can call models, run inference, and chain AI capabilities. With Honeyhive, your agent can call models for generation, classification or extraction inside a workflow.
Q.04
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 Honeyhive access at any time.
Q.05
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 Honeyhive is a configuration step, not an engineering project.
Q.06
Yes. Molted keeps Honeyhive connections healthy for long-running agents, refreshing tokens and surfacing any re-auth, so autonomous workflows that depend on Honeyhive keep running.
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