Audits a sample of HTTP request URLs against explicit, documented cache-key standardization rules...
Audits a sample of HTTP request URLs against explicit, documented cache-key standardization rules (query param drops, query sorting, fragment dropping) and reports which distinct request variants would collapse onto the same proposed cache key. Never fetches or applies anything: it is a bounded, pure computation over the exact samples you provide. Equivalence between merged variants is only ever reported as "observed_equivalent" when every contributing sample carries the same explicit representation_id; otherwise the merge is flagged "conflict" (proven mismatch) or "unproven" (no evidence either way). No hit-rate, revenue, or cache-performance prediction is made, and no CDN/Cloudflare rule is ever read or written. Price: 0.05 USDC per completed bounded job on Base.
| Name | Required | Description | Default |
|---|---|---|---|
| rules | No | ||
| requests | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint=true, idempotentHint=true), the description adds meaningful behavioral detail: it is a bounded pure computation over provided samples, makes no network or CDN side effects, and defines the exact semantics of 'observed_equivalent', 'conflict', and 'unproven' outcomes. It also discloses pricing. No statement contradicts the annotations.
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 purpose is front-loaded in the opening clause, and every subsequent sentence adds a distinct piece of value: scope boundaries, verdict semantics, exclusions, and pricing. The description is detailed but not padded, with no redundant restating of the name or title.
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?
Even without an output schema, the description defines the observable output categories and the conditions under which each is produced. Combined with the annotations and input schema, this gives an agent enough context to decide whether to call the tool and how to interpret the result. The exact report shape is not specified, but the essential semantics are covered.
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 0%, so the description must compensate. It explains the rules object via query param drops, query sorting, and fragment dropping, and it clarifies the critical role of representation_id in determining equivalence verdicts. It does not explain count or method, but those are secondary to the tool's core behavior.
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 first sentence states a specific verb ('Audits') and a precise resource: HTTP request URLs are checked against cache-key standardization rules and the tool reports which variants collapse onto the same proposed key. This clearly distinguishes it from generic URL utilities or cache-performance tools. The description is self-contained and matches the tool's name.
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 positive use case is explicit: audit request samples against cache-key standardization rules. The description also gives explicit when-not guidance: it never fetches or applies anything, makes no hit-rate/revenue/performance predictions, and reads or writes no CDN/Cloudflare rules. This helps an agent avoid selecting it for tasks outside its scope.
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. Dates show when Glama detected each change.
cache_key_explosion_auditorClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Rule-based site audits: accessibility, SEO, security headers, performance. Metered per call.
URL reality check for agents: status, content hash, classification, wayback fallback.
Deterministic acceptance report for a supplied product catalog: validates price/currency/availabi...
Validate HTML/CSS, audit SEO and JSON-LD, check links, and capture responsive screenshots.
Add one secure layer between your agents and this server.
Only a single tool exists, so there is no possibility of selecting the wrong tool. The tool's purpose is clearly and narrowly defined, making the surface unambiguous.
With one tool there is no naming pattern to conflict with; the name 'cache_key_explosion_auditor' is descriptive, consistent in style, and clearly signals its function.
At one tool it is slightly below the typical 3-15 range, but the server's scope is extremely narrow and the single tool fully encapsulates the audit task. The minimal count is reasonable and not excessive.
The tool covers the complete stated workflow: accepting URL samples, applying cache-key rules, and reporting equivalent variants, conflicts, and unproven merges. It intentionally avoids fetching/applying, so no operations are missing for its defined domain.
