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DevHelm MCP Server

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by devhelmhq

create_monitor

Creates a new uptime monitor supporting HTTP, DNS, TCP, ICMP, MCP Server, and Heartbeat checks. Configure name, protocol type, and check frequency to monitor service availability.

Instructions

Create a new uptime monitor.

Required fields: name, type (HTTP/DNS/TCP/ICMP/MCP/HEARTBEAT), config (type-specific), frequencySeconds (30-86400).

managedBy is set automatically to MCP server-side; callers cannot override it. Use the SDK or CLI directly if you need a different attribution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes``CreateMonitorRequest`` with ``managed_by`` hidden from MCP callers. The MCP server *always* sets ``managedBy="MCP"`` on the API call so the dashboard can attribute the monitor to its real origin (an AI agent), rather than letting the LLM thread an arbitrary value through. This subclass: 1. Re-declares ``managed_by`` as optional (``default=None``) so a body that omits it passes Pydantic validation — the parent class makes the field required, which would force the LLM to set it. 2. Marks the field with ``exclude=True`` so any value the LLM does smuggle in via a permissive client never reaches ``model_dump()``. The server-side ``managedBy`` injection in :func:`create_monitor` is the only writer that survives the boundary. The field is also stripped from the JSON Schema FastMCP advertises (see ``server.py`` post-registration step), so well-behaved LLMs never see ``managedBy`` as a callable parameter at all.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It explains that managedBy is auto-set server-side, which is a key trait. However, it mentions a frequency range of 30–86400 while the schema uses 10–86400, causing a minor inconsistency. It does not discuss side effects, idempotency, or other behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loading the purpose and required fields, then adding a behavioral note and alternative. Every sentence is essential and there is no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (many nested objects, assertions, incident policies), the description is minimal. It covers the essential required fields but does not hint at the extensive configuration options available. The output schema exists, so return values are not needed, but more context would help the agent understand the tool's full capabilities.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so the description adds limited value. It summarizes required fields (name, type, config, frequencySeconds) but misstates the frequency minimum (30 vs. 10). The schema itself provides thorough parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description starts with 'Create a new uptime monitor' which clearly states the verb and resource. It lists required fields and distinguishes from siblings by noting that managedBy is auto-set and that the SDK/CLI should be used for different attribution, providing differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when not to use this tool (when different managedBy is needed) and provides an alternative (SDK/CLI). However, it does not provide general guidance on when to choose this over other create_* tools, but the context is clear from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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