Probe an MCP endpoint right now: is it alive, which transport it speaks, how many tools it exposes, and whether its tool schema changed since the last check. Use before depending on a third-party MCP server.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public http(s) URL of the MCP endpoint to inspect. | |
| include_tools | No | Return the full tool list, not just the count. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden of behavioral disclosure. It reveals that the tool performs a live probe, checks multiple runtime aspects, remembers prior checks ('since the last check'), and is intended as a pre-dependency validation. This adds meaningful non-obvious context beyond what the schema shows, though it does not mention potential network latency or failure behavior.
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 two sentences, front-loaded with the core purpose, and every clause provides necessary information. There is no fluff or repetition.
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?
The tool has no output schema, so the description must communicate what the caller gets. It does so by enumerating the probe results (alive, transport, tool count, schema change). It does not detail exact response fields or error cases, but for a moderate-complexity health probe this is reasonably complete.
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 parameters are already well-documented in the schema. The description adds general context about probing and schema-change detection but does not add parameter-specific meaning beyond what the schema already provides. Baseline 3 is appropriate.
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 specifies a concrete action ('Probe an MCP endpoint right now') and enumerates the exact outputs: liveness, transport, tool count, and schema-change detection. It distinguishes itself from siblings like check_schema_drift by positioning itself as a broader initial readiness probe rather than a focused drift 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 an explicit use case: 'Use before depending on a third-party MCP server.' This is clear contextual guidance, though it does not name sibling tools or state when not to use it, so it falls slightly short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct: get_known_tools and get_uptime read history, while check_mcp_endpoint is a general live probe. The only potential confusion is between check_mcp_endpoint and check_schema_drift, as both involve schema changes, but their descriptions clarify that one is a broad health check and the other is a focused diff.
All tool names follow a consistent verb_noun pattern: check_ for active probes and get_ for historical retrievals. This makes the tool's behavior predictable from its name.
Four tools is well-scoped for a validator/monitoring server, covering live checks and historical reads without unnecessary bloat.
The server covers live probing, schema drift detection, and historical views of tools and uptime. A minor gap is the lack of a tool to list all monitored endpoints or manage snapshots, but for the stated purpose the core operations are present.