Ask your AI about any brand's claim-vs-reality coherence. NES (Net Entropy Score) gives a website brand-consistency score (the claim), recent public news (the reality), and the divergence between them. Tools: get_brand_coherence and compare_brands. Directional read from public signal, not a fraud or financial check. Free.
Scored across 2 tools
Each tool has a clearly distinct purpose: one compares multiple brands side by side, while the other retrieves detailed coherence data for a single brand. No overlap or ambiguity.
Both tools follow a consistent verb_noun pattern (compare_brands, get_brand_coherence), using snake_case throughout. The naming is predictable and clear.
With only 2 tools, the server feels minimal for the domain of brand coherence signals. Additional tools for scanning new brands or listing available brands would enhance coverage, but the current count is borderline acceptable.
The server lacks essential operations: there is no way to scan or add a new brand to the database, nor list which brands are already scanned. Users are limited to querying existing data, leaving clear gaps that hinder full workflow completion.
Compare the NES coherence signal for several brands side by side (claim, reality, divergence for each). Presents the data; it does NOT recommend one brand over another. The caller decides.
| Name | Required | Description | Default |
|---|---|---|---|
| urls | Yes | Brand URLs or domains to compare (up to 8). |
| Name | Required | Description |
|---|---|---|
| brands | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear the full burden. It accurately describes the non-recommending behavior and the data presentation, but does not mention read-only nature or any other side effects, which is acceptable for a data presentation 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 sentences, concise and front-loaded with the main purpose. No redundant information. Every word contributes.
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 the output schema exists (unseen but present) and the simplicity of input, the description sufficiently covers the tool's purpose and constraints. It could mention the output format briefly, but completeness is adequate.
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%, baseline 3. The description adds value by specifying the limit of up to 8 URLs and clarifying that they are brand URLs or domains, which goes beyond the schema's 'Brand URLs or domains to compare'.
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 compares brands side-by-side for NES coherence signal, listing specific outputs (claim, reality, divergence). This distinguishes it from sibling get_brand_coherence, which presumably handles a single brand.
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 explicitly states it presents data and does not recommend, guiding the agent to use it when only data is needed. It does not explicitly mention when to use the sibling tool, but the contrast is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get the NES claim-vs-reality coherence signal for one brand: its website coherence score (the claim), recent public reality (matched news events), and the divergence between them. High divergence means the brand presents as coherent while its reality is turning negative. Directional opinion from public signal; not a fraud or financial check. Returns 'no read on file' for brands never scanned.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Brand website URL or domain, e.g. https://acme.com | |
| brand | No | Brand name, used if no URL is given. |
| Name | Required | Description |
|---|---|---|
| brand | No | |
| claim | No | What the brand says about itself via its website. |
| reality | No | |
| divergence | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses return fields, the 'no read on file' case, and its nature as public directional signal. Lacks explicit read-only guarantee but is otherwise transparent.
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?
Three sentences, no redundancy. Front-loaded with main action, each sentence adds value. Very concise.
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?
Complete for its complexity. With output schema present, description explains key return values and edge case. Parameter coverage 100%, sibling listed. No gaps.
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 covers 100% of parameters. Description adds meaning by stating 'used if no URL is given' for brand parameter, clarifying mutual exclusivity. This goes beyond the bare schema.
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 'NES claim-vs-reality coherence signal for one brand' with specific components (coherence score, reality, divergence). It distinguishes from sibling 'compare_brands' by focusing on a single brand.
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?
It specifies when to use (for one brand's coherence), notes the 'no read on file' edge case, and clarifies it's directional opinion, not fraud/financial check. No explicit when-not-to-use or alternative beyond sibling name.
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.
compare_brandsget_brand_coherenceClaiming 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!
