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Glama

SRI — MCP Server Inspector

What has already been read, and what was found in it

get_corpus_coverage
Read-only

No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface).

Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
not_readYesRetrieved but contained no implementation code. Not 'clean' - there was nothing to read.
categoriesYesShare of judged servers with at least one finding in the category. Counted per server, not per finding. Most findings describe the server's stated job.
disclaimerYes
lookup_toolNo
servers_readYesRead at source level and judged.
analyzer_versionNo

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already include readOnlyHint: true, but the description adds significant transparency beyond that: 'No arguments', 'Returns how many... and the share of them with each category', and explicitly states limitations: 'aggregate counts only - no per-server findings, and no verdict about any individual server.' This fully clarifies behavioral scope.

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 extremely concise—two sentences. The first sentence states the function, and the second gives usage context and limitations. No filler or redundant phrases. It is front-loaded with the key information and every sentence adds value.

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

Completeness5/5

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

Given the tool's simplicity (no params, simple aggregate output), the description fully covers what it does, how to use it, and what it doesn't do. The existence of an output schema covers the return format, so the description doesn't need to detail that. It is complete and actionable.

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

Parameters4/5

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

There are zero parameters, and the schema is empty with 100% coverage. The description even states 'No arguments', which aligns with the schema. Since there are no parameters to explain, a baseline of 4 is appropriate; the description doesn't need to add param semantics.

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 clearly states the tool's function: 'Returns how many MCP servers have been read at source level, and the share of them with each category of finding.' It also differentiates from the sibling tool by explicitly noting it provides only aggregate counts with 'no per-server findings', making its purpose distinct.

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

Usage Guidelines5/5

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

The description gives explicit guidance: 'Use this to judge whether checking a specific server is worth it before you look one up.' It also implicitly contrasts with the sibling tool by stating it does not give per-server details, which orients the agent on when to use this vs. check_mcp_server.

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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Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.9/5.0
Disambiguation5/5

The two tools serve clearly distinct purposes: one checks a specific MCP server's source-level behavior, while the other provides aggregate corpus coverage statistics. There is no overlap or realistic chance of selecting the wrong tool.

Naming Consistency5/5

Both tool names follow a consistent verb_noun pattern with snake_case: check_mcp_server and get_corpus_coverage. The naming convention is uniform and immediately signals what each tool does.

Tool Count4/5

Two tools is slightly below the typical 3-15 range, but the server has a narrow, focused purpose and each tool earns its place in the workflow. The count feels intentional rather than incomplete.

Completeness5/5

For the stated domain of inspecting MCP servers before connection, the surface is complete: get_corpus_coverage gives corpus-level context, and check_mcp_server gives the per-server inspection. There are no dead ends or missing lifecycle steps.