TopFood publishes digital restaurant menus with QR codes. Give it a menu (text, photo transcription, or description) and it creates a live, shareable menu page the restaurant owner can claim for free — no signup required upfront.
Scored across 2 tools
The two tools have clearly separate purposes: one creates a restaurant menu and the other reports platform issues. There is no overlap or ambiguity in choosing between them.
Both tool names use the same snake_case verb_noun pattern: create_restaurant_menu and report_problem. Naming is consistent and predictable.
With only two tools, the server feels very thin, but each tool serves a distinct role: one primary domain operation and one generic feedback channel. It is borderline but not unreasonable for such a narrow purpose.
The domain surface only supports creating a menu; there are no tools to list, update, retrieve, or delete menus. Common lifecycle actions would cause obvious agent failures, and the report_problem tool is only a manual fallback rather than a real management operation.
Sends a bug report or product feedback about TopFood to the maintainers. Use it when a tool call fails unexpectedly, when the published menu is wrong or incomplete, or when the restaurant owner tells you something is broken or missing. Do NOT use it for input that a tool already rejected with a clear explanation — fix the input and retry instead. Describe what was attempted, what happened, and what was expected. Reports are read by people and there is no reply channel: tell the user the report was sent, and that they should include an email address in the message if they want an answer.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | What happened, what was expected, and what the user was doing. Write it for a developer who cannot see this conversation. Include the user's own words when they reported it. | |
| category | Yes | bug = something is broken; missing_feature = something the user needs does not exist; confusing = it works but was unclear; pricing = about plans or cost; other = anything else. | |
| claim_url | No | The claim link returned by create_restaurant_menu, when the report is about a menu that was created in this conversation. It attaches the report to that restaurant. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false and minimal, so the description carries the burden. It discloses that reports are read by people, there is no reply channel, and the user should be told the report was sent. It even advises including an email address for a response. This is rich behavioral context beyond 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 description is three sentences, each earning its place: first defines purpose, second gives usage rules, third explains human-read behavior and follow-up steps. It is front-loaded and free of fluff.
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 3-parameter tool with no output schema and sparse annotations, the description covers purpose, usage, behavioral notes, and user-facing instructions. It doesn't explicitly state the return value, but the instruction to tell the user the report was sent implies the outcome. Minor gap: no mention of idempotency or retry behavior, but not essential here.
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 baseline is 3. The description adds value by instructing what to include in the message ('what was attempted, what happened, what was expected') and advising to include an email address, which enriches the meaning of the message parameter without repeating schema details.
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 specific verb and resource: 'Sends a bug report or product feedback about TopFood to the maintainers.' It clearly distinguishes from the sibling tool create_restaurant_menu, which is about creating menus rather than reporting issues.
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 when-to-use scenarios are listed ('when a tool call fails unexpectedly', 'published menu is wrong', etc.) and a direct exclusion is given: 'Do NOT use it for input that a tool already rejected with a clear explanation — fix the input and retry instead.' This provides strong decision guidance.
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.
create_restaurant_menureport_problemClaiming 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.
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