watchgoose-mcp
Summary: This server provides read-only access to Watchgoose cron/recurring-task monitoring data for a project — checks and their status history.
List checks (
list_checks) — optionally filtered by exactslug, requiredtags, andlimit(1–100); returns names, status, schedule, timeout/grace, channels, last/next ping, ping counts.Get one check (
get_check) — fetch a single check by its stable 40-characterunique_keywith full current state and schedule (cron/OnCalendar use schedule + grace; simple checks use timeout + grace).List status changes (
list_flips) — retained flips for a check, newest first, with optionalstart/end(Unix seconds) orsecondslookback andlimitup to 200;up: 1means the check became up.Read-only and idempotent — all three tools are marked read-only, non-destructive, closed-world; no mutation, ping, or integration tools appear in this schema.
Writes exist but are not exposed here — per the README,
list_pings,list_channels,create_check,update_check,pause_check,resume_check, anddelete_checkrequire anhcw_read-write key andWATCHGOOSE_ENABLE_WRITES=true.Bounded, privacy-trimmed output — results are capped (100 checks, 200 flips) and truncated with
metacounts; UUIDs, ping URLs, IPs, and unknown API fields are stripped.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@watchgoose-mcpshow me the status of all my cron job checks"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Watchgoose MCP
Watchgoose MCP connects MCP-capable AI clients to the Watchgoose Management API. It lets you inspect cron and recurring-task monitoring, with check changes available only when you explicitly enable writes.
Hosted connector
Use the hosted Streamable HTTP endpoint in clients that support OAuth 2.1 and Dynamic Client Registration:
https://mcp.watchgoose.com/mcpAvailable in
Watchgoose is available in the Claude connector directory.
Watchgoose is listed in ChatGPT plugins for GPT and Codex.
Watchgoose is listed in the official MCP Registry.
The watchgoose-mcp package is available on npm.
In Claude, open Settings > Connectors and add the endpoint as a custom connector. For Claude Code, run:
claude mcp add --transport http --scope user watchgoose https://mcp.watchgoose.com/mcpThe browser consent flow limits each connection to one project and defaults to read-only access. See the Watchgoose MCP documentation for the tool and privacy boundaries.
Related MCP server: uptimepage
Requirements
Node.js 20 or later
A project-scoped Watchgoose API key from Project settings → API Access → Create (read-only)
Use an hcr_ read-only key when you only need check state and status history. Use an hcw_
read-write key when you also need pings, integrations, or check changes.
Claude Desktop
Add this entry to claude_desktop_config.json and restart Claude Desktop:
{
"mcpServers": {
"watchgoose": {
"command": "npx",
"args": ["-y", "watchgoose-mcp"],
"env": {
"WATCHGOOSE_API_KEY": "hcr_your_project_key"
}
}
}
}Claude Code
claude mcp add --env WATCHGOOSE_API_KEY=hcr_your_project_key \
--transport stdio --scope user watchgoose -- npx -y watchgoose-mcpRun claude mcp get watchgoose to check the connection.
Cursor
Create .cursor/mcp.json in your project, or add the same entry to your user MCP configuration:
{
"mcpServers": {
"watchgoose": {
"command": "npx",
"args": ["-y", "watchgoose-mcp"],
"env": {
"WATCHGOOSE_API_KEY": "hcr_your_project_key"
}
}
}
}VS Code
Create .vscode/mcp.json:
{
"servers": {
"watchgoose": {
"type": "stdio",
"command": "npx",
"args": ["-y", "watchgoose-mcp"],
"env": {
"WATCHGOOSE_API_KEY": "hcr_your_project_key"
}
}
}
}Run MCP: List Servers and start watchgoose.
Environment
Variable | Required | Default | Description |
| Yes | - | Project-scoped |
| No |
| Management API base URL. HTTPS is required except for loopback development hosts. The key is sent to this host, so use only a URL you trust. |
| No |
| Set to |
| Legacy keys only | - | Required as |
The server classifies key prefixes locally and never probes the API to infer access. Setting
WATCHGOOSE_ENABLE_WRITES=true cannot give a read-only key additional access.
Tools
Checks are addressed by stable 40-character unique_key values. UUIDs, ping URLs, and integration
UUIDs are used only inside the server and are not shown to the AI client.
Tool | Required access | Management API mapping |
| Read-only |
|
| Read-only |
|
| Read-only |
|
| Read-write | Resolve |
| Read-write |
|
| Read-write plus writes enabled |
|
| Read-write plus writes enabled | Resolve |
| Read-write plus writes enabled | Resolve |
| Read-write plus writes enabled | Resolve |
| Read-write plus writes enabled | Resolve |
Integration assignments use exact integration names. Names must be non-empty and unique within the project.
create_check is a create-or-update operation when unique is supplied: a matching existing check
has its supplied settings replaced. timeout without schedule also switches a scheduled check to
interval monitoring: the stored schedule string remains, but no longer governs cadence. Include the
confirmed schedule to retain scheduled monitoring. Other omitted settings remain unchanged.
channels: [] clears all alert integration assignments. The tool therefore advertises
destructiveHint: true. A new check awaits success/failure for completion-based cadence; a first
failure can move it down. An optional start ping can initiate runtime monitoring before completion.
List results are capped at 100 checks, 100 pings, 200 flips, and 100 integrations. Every serialized tool result is also capped at 24,000 characters. Results include metadata when entries are omitted.
Security
Writes are disabled by default, even with an
hcw_key.The API key is sent only in the
X-Api-Keyheader and is never logged or returned.API redirects are rejected so credentials cannot be forwarded to another host.
Check UUIDs, ping and update URLs, integration UUIDs, and unknown future API fields are removed from output.
Pings keep only
type,date,n,scheme,method, andduration. Source IP addresses, user agents, run IDs, and body URLs are removed.Ping bodies are never requested.
The server has no telemetry.
Protect client configuration files that contain API keys. Prefer a dedicated project and the least-privileged key that exposes the tools you need. Revoke a key from Watchgoose project settings when it is no longer in use.
Workflow skills
The repository includes portable skills for auditing scheduled-job coverage, drafting single-job setup, triaging missed heartbeats, reviewing existing monitoring health, and proposing approved create-only batches from an audit, list or CSV. See the skills guide for local installation, examples, and safety boundaries. Skills do not grant additional access, automatically run jobs, or change the existing directory listings.
Development
npm install
npm run format:check
npm run lint
npm run typecheck
npm test
npm run publish:dry-runProduction integration tests are opt-in and require dedicated test-project keys. They never run in CI.
License
MIT
Various badges
Available Tools
3 toolsget_checkGet a Watchgoose checkARead-onlyIdempotentInspect
Get one check by its stable unique_key, including its current state and schedule. Cron and OnCalendar checks use schedule plus grace; simple checks use timeout plus grace.
| Name | Required | Description | Default |
|---|---|---|---|
| unique_key | Yes | 40-character stable check identifier from list_checks. |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | No | |
| check | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds useful behavioral detail beyond annotations: it returns current state and schedule, and explains that Cron/OnCalendar checks use schedule plus grace while simple checks use timeout plus grace.
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 sentences with no redundancy. The primary purpose and identifier are front-loaded, and the second sentence adds meaningful behavioral nuance without unnecessary detail.
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?
For a single-parameter read tool with strong annotations and an output schema, the description sufficiently explains what the tool does, what it returns, and the relevant scheduling nuance. Nothing essential is missing.
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 the schema already documents unique_key as a 40-character stable identifier from list_checks. The description repeats 'stable unique_key' but adds no new parameter semantics beyond what the schema provides, so the baseline 3 applies.
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 states a specific verb ('Get'), resource ('one check'), identifier ('stable unique_key'), and the content returned ('current state and schedule'). It clearly distinguishes from siblings: list_checks lists checks, while this retrieves a single one.
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?
The description gives clear context: use this tool when you need a single check by its unique_key, not a list. It does not explicitly exclude alternatives, but the 'one check by its stable unique_key' phrasing implies the appropriate use case, and the schema parameter notes the key comes from list_checks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_checksList Watchgoose checksARead-onlyIdempotentInspect
List checks in this Watchgoose project, optionally filtered by slug or tags. A successful ping arms a new check; Watchgoose then expects the next success within its timeout or schedule plus grace period.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | Exact check slug to match, using lowercase letters, numbers, hyphens, or underscores. | |
| tags | No | Tags that every returned check must have, for example ["production", "backup"]. | |
| limit | No | Maximum number of checks to return, from 1 to 100. |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | Yes | |
| checks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful domain context about how pings arm checks and expectations after timeout/schedule plus grace period, but it does not disclose tool-specific behavior such as sorting, pagination, or response shape beyond the existing schema.
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?
The description is compact and front-loaded: the first sentence states the action, resource, and filters. The second sentence is concise and adds useful domain context, though it is somewhat tangential to actually invoking list_checks.
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?
For a low-complexity, read-only list operation with a fully described input schema, an output schema, and complete annotations, the description is largely sufficient. It specifies project scope and filtering, though explicit sibling differentiation would make it fully self-contained.
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%, with slug, tags, and limit each already described in the input schema. The description only restates the slug/tags filter idea and adds no parameter-level meaning beyond what the schema provides, so the baseline score of 3 applies.
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 opens with a precise action and resource: 'List checks in this Watchgoose project'. It also states the optional filters (slug or tags), and the collection-scope wording naturally distinguishes this from the sibling tools get_check and list_flips.
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?
The description implies usage through 'optionally filtered by slug or tags', but it never explicitly contrasts this tool with get_check or list_flips. There is no when-to-use vs. alternatives guidance, only a clear statement of what the tool does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_flipsList a check's status changesARead-onlyIdempotentInspect
List retained status changes for a check, newest first, with optional time filters. In results, up: 1 means the check became up; up: 0 means any other status, including down, paused, and new after resume. A pause or resume that changes the check's status records a flip.
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | Exclusive upper bound for status-change timestamps, as Unix seconds; for example 1592217980. | |
| limit | No | Maximum number of status changes to return, from 1 to 200. | |
| start | No | Inclusive lower bound for status-change timestamps, as Unix seconds; for example 1592214380. | |
| seconds | No | Lookback window for status changes in seconds, from 0 to 31536000; for example 3600. | |
| unique_key | Yes | 40-character stable check identifier from list_checks. |
Output Schema
| Name | Required | Description |
|---|---|---|
| meta | Yes | |
| flips | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnly/idempotent annotations, the description explains key output semantics: up: 1 means became up, up: 0 includes down/paused/new-after-resume, and pause/resume that changes status records a flip. This materially helps an agent interpret results and is not visible in the schema alone.
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?
The description is compact and front-loaded with the core operation, followed by the essential semantics of the up field and flip recording. Every sentence contributes useful information with no redundancy.
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 annotations and an output schema present, the description sufficiently covers what the tool returns, how results are ordered, and what counts as a flip. The required unique_key and optional time filters are documented in the schema, so nothing critical is missing for invoking the tool correctly.
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%, so the schema already documents all five parameters. The description adds only the general notion of 'optional time filters,' which aligns with start/end/seconds but provides no additional parameter-level meaning beyond the schema.
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 uses a specific verb and resource: 'List retained status changes for a check.' It also states the ordering ('newest first') and clearly distinguishes this tool from siblings by focusing on status-change history rather than listing checks or fetching a single check.
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?
The description gives clear context: use this when you need a check's status changes with optional time filters. It does not explicitly name alternatives or say when not to use it, but the operation is distinct enough from list_checks and get_check that the intended use is evident.
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.
3 tool updates
v1.0.1- Changed
get_check1 field changed- added
Input schema / properties / unique_key / descriptionAdded value: +"40-character stable check identifier from list_checks."
- Changed
list_checks3 fields changed- added
Input schema / properties / limit / descriptionAdded value: +"Maximum number of checks to return, from 1 to 100." - added
Input schema / properties / slug / descriptionAdded value: +"Exact check slug to match, using lowercase letters, numbers, hyphens, or underscores." - added
Input schema / properties / tags / descriptionAdded value: +"Tags that every returned check must have, for example [\"production\", \"backup\"]."
- Changed
list_flips5 fields changed- added
Input schema / properties / end / descriptionAdded value: +"Exclusive upper bound for status-change timestamps, as Unix seconds; for example 1592217980." - added
Input schema / properties / limit / descriptionAdded value: +"Maximum number of status changes to return, from 1 to 200." - added
Input schema / properties / seconds / descriptionAdded value: +"Lookback window for status changes in seconds, from 0 to 31536000; for example 3600." - added
Input schema / properties / start / descriptionAdded value: +"Inclusive lower bound for status-change timestamps, as Unix seconds; for example 1592214380." - added
Input schema / properties / unique_key / descriptionAdded value: +"40-character stable check identifier from list_checks."
3 tool updates
v1.0.0- First observed
get_check - First observed
list_checks - First observed
list_flips
TDQS
Scored across 3 tools
The three tools are clearly distinct: list checks, get a single check by key, and list status changes. There is no meaningful overlap or ambiguity between them.
All tool names follow a consistent lowercase verb_noun pattern: list_checks, get_check, list_flips. The singular/plural difference is natural and appropriate.
Three tools is well-scoped for a read-only monitoring server. Each tool provides a distinct capability with no redundancy or filler.
The read-only monitoring surface is coherent: discover checks, inspect a check, and view its flip history. Check management and ping actions appear to happen outside MCP, so the lack of mutation tools is a minor gap rather than a fatal one.
Maintenance
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