alertchecker-mcp
Server Details
Create AI-monitored web alerts from plain English — just say "Alert me when..."
- Status
- Healthy
- Uptime
- 8.1% over 36 days
- OAuth
- Works in Glama
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- steve-chambers/alertchecker-mcp
- GitHub Stars
- 0
TDQS
Scored across 1 tool
With only a single tool, there is no possibility of ambiguity or overlap. The tool's purpose is clearly defined and distinct by default.
The single tool name 'create_alert' follows a clean verb_noun pattern. Since there are no other tools, the naming is trivially consistent.
One tool is at the very low end of a reasonable count. For a server that monitors the web and sends notifications, a single tool feels thin but is not entirely unreasonable for a focused use case.
The server only supports creating alerts, with no way to list, retrieve, update, delete, or disable them. This severely incomplete surface leaves agents unable to manage alerts after creation, leading to likely failures in any non-trivial workflow.
Available Tools
1 toolcreate_alertCreate alertAInspect
Create an AlertChecker alert that monitors the web and notifies the user by email when a statement becomes true or the answer to a yes/no question changes to yes. Use disableAfterNotification=false only when the user explicitly asks for a recurring alert or to keep checking after notifying.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | A short, human-readable title for the alert, e.g. 'iPhone 16 Pro restock'. | |
| statement | Yes | The condition to check for and get alerted on, phrased as a factual statement or yes/no question, e.g. 'The iPhone 16 Pro is back in stock at apple.com' or 'Is the iPhone 16 Pro back in stock at apple.com?'. | |
| disableAfterNotification | No | Whether to disable the alert after it sends a notification. Omit or set true for a normal alert. Set false only when the user explicitly asks for a recurring alert or to keep checking after notifying. |
Output Schema
| Name | Required | Description |
|---|---|---|
| id | Yes | The AlertChecker alert identifier returned by the creation flow, e.g. alert_123. |
| status | Yes | The alert status after creation: active or pending_verification. |
| needsVerification | Yes | Whether the alert still needs account email verification before it becomes active. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as a write operation (readOnlyHint=false, idempotentHint=false), and the description adds the observable behavior of web monitoring and email notification. It could disclose that repeated calls create separate alerts, but the idempotentHint covers that signal and no contradiction exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two front-loaded sentences with no filler. The second sentence is slightly redundant with the disableAfterNotification schema description, so it is not perfectly lean, but it is appropriately sized overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema, full parameter coverage, and no sibling tools, the description plus schema gives an agent enough to call the tool correctly. The only small omission is not explicitly stating that each call creates a distinct alert, which is already implied by the annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and each parameter already has a meaningful description, so the baseline applies. The description reinforces the disableAfterNotification guidance, but that is also present in the schema, so it adds no new parameter-level meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Create'), a resource ('AlertChecker alert'), and a concrete monitoring/notification behavior: watch the web and email when a statement becomes true or a yes/no answer changes to yes. This goes well beyond the title and would let an agent distinguish it from generic alert-creation tools even without siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives explicit when-to-use guidance for the non-default behavior: disableAfterNotification=false only when the user explicitly asks for recurring alerts or continued checking. With no sibling tools listed, there is no alternative to differentiate, so the lack of an exclusion clause is not a real gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- Changed
create_alert1 field changed- changed
Input schema / properties / statement / descriptionPrevious value: -"The condition to check for and get alerted on, phrased as a factual statement, e.g. 'The iPhone 16 Pro is back in stock at apple.com' or 'It will rain in London tomorrow'."New value: +"The condition to check for and get alerted on, phrased as a factual statement or yes/no question, e.g. 'The iPhone 16 Pro is back in stock at apple.com' or 'Is the iPhone 16 Pro back in stock at apple.com?'."
1 tool update
- First observed
create_alert
Related MCP Connectors
Track competitors from your AI assistant: change feed, page snapshots, labels and alerts.
Track prices & price history on any online shop, with alerts and an API
Hiro Radar: AI-assisted monitoring for leads, competitors, opportunities and web changes.
Give an AI agent eyes on the web: turn any feed, page, or stream into deduplicated change events.
Related MCP Servers
- FlicenseNot gradedqualityCmaintenanceEnables AI assistants to monitor web pages for content changes and receive alerts when changes occur.-
- FlicenseNot gradedqualityCmaintenanceEnables monitoring of website changes through contracts, with automatic extraction, semantic diffing, and healing, triggering alerts and actions via email, Slack, or Telegram.-
- AlicenseNot gradedqualityDmaintenanceMonitor any website and get AI-enriched change intelligence via MCP. Manage sources, search changes, and automate web monitoring from Claude, Harvey, or any MCP client.22 npmMIT
- FlicenseNot gradedqualityDmaintenanceEnables monitoring competitor websites for price drops, new products, promotions, and content changes directly from Claude or any MCP-compatible AI client.-
Glama MCP Gateway
Add one secure layer between your agents and this server.