Live status and health checks for AI coding providers: Claude, Cursor, Copilot, Codex and more.
Scored across 2 tools
Both tools serve the same core purpose of checking AI provider availability, and an agent could easily pick either. While ai_provider_status gives raw status details and check_provider_health returns a boolean decision, the boundary is subtle enough to cause misselection.
ai_provider_status is a noun phrase while check_provider_health follows a verb_noun pattern. The inconsistent structure makes the set feel less cohesive, though both use snake_case.
Two tools is on the thin side, but for a narrowly scoped provider-status server it is not unreasonable. The count feels minimal yet not egregiously incomplete.
The domain is simply checking provider status and health, and the two tools together cover both raw status and actionable health checks. Minor gaps like historical uptime or incident detail are not essential for the stated purpose.
Get the live status of AI coding providers (Claude, OpenAI, Copilot, Cursor, OpenRouter and more). Returns status, how long each provider has been in its current state, and last check time. Pass service_id for one provider, omit it for all.
| Name | Required | Description | Default |
|---|---|---|---|
| service_id | No | Optional provider id, e.g. claude, openai, github_copilot, cursor, openrouter |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description transparently discloses the return fields: status, duration, last check time. It implies a read-only operation and is sufficient for a status tool.
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 concise sentences that front-load the purpose and then detail the behavior. No unnecessary words.
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?
Completes the picture without output schema by stating what the tool returns. The simplicity of the tool and high schema coverage make this sufficient.
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?
Adds value beyond the schema by explaining the effect of including or omitting the parameter. Schema coverage is 100%, but the description clarifies usage.
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 clearly states the tool gets live status of AI coding providers, listing examples. It distinguishes from the sibling tool by focus on status rather than health.
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?
Explicitly states how to use the parameter: pass service_id for one provider, omit for all. Could improve by noting when to use check_provider_health instead, but sufficient for a simple tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check whether one or more AI coding providers are healthy enough to use right now. Returns healthy=true only when every requested provider is operational (or within the allowed statuses). Use this before starting work that depends on a provider, or to decide which provider to route to.
| Name | Required | Description | Default |
|---|---|---|---|
| services | Yes | Provider ids to check, e.g. ["claude", "openrouter"] | |
| allow_degraded | No | Treat degraded performance as healthy (default false) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It explains the return condition ('healthy=true only when every requested provider is operational or within allowed statuses'), but lacks details on error handling, rate limits, or network behavior. Adequate but not rich.
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, no waste. Front-loaded with purpose, then usage. Every sentence is necessary and informative.
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?
Given low complexity (2 params, no output schema, no annotations), the description is largely complete. It explains purpose, usage, and basic behavior. Missing explicit return format details (e.g., exact JSON structure) but not critical for a boolean health check.
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 coverage is 100%, so baseline 3. Descriptions for both parameters exist in the schema; the tool description does not add meaningful extra meaning beyond restating those definitions.
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 ('check') and resource ('provider health'), clearly stating it returns healthy=true only when all requested providers are operational. It distinguishes from sibling tool ai_provider_status by focusing on aggregated multi-provider health checks.
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?
Explicit guidance on when to use: 'before starting work that depends on a provider, or to decide which provider to route to.' Does not mention when not to use or explicitly compare with sibling, but context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
ai_provider_statuscheck_provider_healthLive status, API pricing and rate limits for ChatGPT, Claude, Gemini, Cursor and 42+ AI tools.
Real-time status for 75+ AI services (OpenAI, Anthropic, Cursor). No auth, CORS-enabled.
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Monitoring + status pages set up by talking to Claude. Auto-detects 30+ SDKs and your URLs.
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