Read-only MCP connector for The Dose Guy source-linked peptide and compound database. Search 260+ compounds, compare vendors and prices, inspect ranking evidence, and retrieve canonical page links. No authentication required.
Live offers for one published compound, one best offer per vendor, sorted by price per mg ascending (blends and unpriceable products last). Prices are integer minor units plus display strings.
| Name | Required | Description | Default |
|---|---|---|---|
| compoundSlug | Yes | Compound slug, e.g. "retatrutide" |
| Name | Required | Description |
|---|---|---|
| note | No | |
| offers | Yes | |
| compound | Yes | |
| compoundUrl | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, and idempotentHint=true, so the safety profile is covered. The description adds valuable behavioral context: results are 'live', sorted by price per mg ascending, with blends and unpriceable products placed last, and prices are integer minor units plus display strings. This goes well beyond the annotations and helps the agent interpret results.
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 a single, dense sentence that packs in all essential details: live nature, one offer per vendor, sorting, placement of blends/unpriceable products, and price format. There is no fluff or repetition; every clause adds information.
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 is simple (one parameter, output schema exists), and the description covers the key behavioral aspects. It does not mention error cases (e.g., compound not found or not published), but the presence of an output schema likely defines return values. Given the low complexity and strong annotations, the description is nearly complete, just missing edge-case guidance.
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?
The input schema has 100% description coverage for the single parameter compoundSlug, providing an example. The description adds no additional parameter-specific meaning (e.g., format, constraints, or default behavior), so it meets the baseline but does not exceed it.
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 states a specific verb (best_vendors_for) and resource (a compound), and clarifies the result set: live offers, one per vendor, sorted by price per mg. This clearly distinguishes it from siblings like get_compound (compound details), list_vendors (vendor list), and search_compounds (compound search).
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 implies usage (when you want vendor offers for a specific compound) but does not explicitly contrast with alternatives or state when not to use it. It lacks phrases like 'for compound details use get_compound' or 'for all vendors use list_vendors', leaving the agent to infer context from sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Full record for one published compound by slug: aliases, category, evidence tier, routes, typical protocol, half-life, status line, canonical URL.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Compound slug, e.g. "retatrutide" |
| Name | Required | Description |
|---|---|---|
| compound | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description does not need to repeat those. The description adds no behavioral context beyond what the schema and output schema already provide (e.g., error behavior, pagination). It is consistent with annotations, so no contradiction, but it adds little extra value.
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 a single sentence that front-loads the core action ('Full record for one published compound by slug') and then lists returned fields. It is efficient and easy to parse, though the field list is a bit lengthy; still, it avoids redundancy and is well-structured.
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 simple get-by-slug tool with an output schema and annotations covering readOnly/idempotent behavior, the description is largely complete. It tells the agent what it returns and how to identify the compound. Missing explicit usage guidance is a minor gap, but overall the tool is well-specified.
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?
The schema covers the single 'slug' parameter with a clear example, and the description merely repeats 'by slug' without adding further semantics. With 100% schema coverage, the baseline of 3 applies; the description does not enhance parameter understanding.
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's purpose: it gets a full record for one published compound by slug, listing the specific fields returned. This distinguishes it from siblings like search_compounds and list_vendors, making the tool's role unambiguous.
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 implies usage (when you have a slug and need a full record), but it does not explicitly mention alternatives or when not to use it. There is no comparison to siblings like search_compounds or best_vendors_for, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Every tracked vendor that is currently alive: DOSE SCORE (when reviewed), liveness status, last-verified date, trust chips, canonical review URL.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| vendors | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds value by specifying exactly what data is returned (DOSE score with condition, liveness status, last-verified date, trust chips, canonical URL) and clarifies the liveness filter, which is beyond the structured metadata. No contradiction with 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?
A single sentence with a clear subject and a colon-separated list of output fields. It is front-loaded with the core action ('Every tracked vendor that is currently alive') and wastes no words. Perfectly 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?
The tool is a simple no-parameter list operation. An output schema exists, so return structure is already documented. The description explains what 'alive' means and lists the fields, which is sufficient for an agent to decide to call it. It does not mention sorting, pagination, or limits, but these are not essential for a basic listing tool and are likely covered by the output schema.
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?
The tool has zero parameters, and schema coverage is 100% (empty properties). The baseline for no parameters is 4, and the description adds no parameter info because there are none. The description's field list effectively describes the output, which is not part of parameter semantics.
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 states a specific verb ('list'), a resource ('vendors'), and a precise scope ('currently alive'), distinguishing it from siblings like best_vendors_for (which implies ranking) and search_compounds (which is search-oriented). It also enumerates the returned fields, making the tool's purpose unmistakable.
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 does not mention when to use this tool versus alternatives. It does not explicitly state that this is the generic listing tool for all alive vendors, nor does it exclude scenarios better served by best_vendors_for or search_compounds. Usage guidance is entirely absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Case-insensitive search over published compound names and aliases (brand names, research codes, shorthand like "reta"). Returns the top 10 matches.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Name or alias fragment, e.g. "reta" or "Mounjaro" |
| Name | Required | Description |
|---|---|---|
| results | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the operation as read-only and idempotent. The description adds valuable behavioral context beyond that: case-insensitive matching, restriction to published compounds, and a fixed top-10 result cap. No contradiction exists between the description and 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 a single sentence that front-loads the most important behavior (case-insensitive search) and packs in the resource scope, alias examples, and result limit without waste. Every element earns its place.
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 simple one-parameter search tool with an output schema and safety annotations, the description covers all necessary context: what is searched, how matching behaves, and how many results are returned. No significant gaps remain for an agent to invoke it correctly.
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 query parameter is already well documented. The description adds little beyond the schema, only reinforcing the notion of aliases and case-insensitivity. This meets the baseline for high schema coverage without needing additional compensation.
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 states a specific action ('search'), a clear resource ('published compound names and aliases'), and concrete result behavior ('Returns the top 10 matches'). It also distinguishes itself from sibling tools by focusing on flexible name/alias lookup rather than vendor listing or exact compound retrieval.
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 provides clear context for when to use the tool: when the agent needs to find compounds by name or alias fragment, including shorthand like 'reta'. It does not explicitly name alternatives or exclusions, but the search-oriented scope is evident enough for correct selection in most cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claiming 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 or an account that owns the GitHub organization, then choose Claim with GitHub.
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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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Each tool serves a clearly distinct purpose: search_compounds discovers compounds, get_compound retrieves compound details, best_vendors_for fetches offers for a compound, and list_vendors lists vendors. There is no meaningful overlap or ambiguity between them.
Three tools follow a clean verb_noun pattern (get_compound, list_vendors, search_compounds), but best_vendors_for breaks the pattern by using a descriptive phrase without a leading verb. Overall naming is still snake_case, readable, and mostly predictable.
Four tools is a well-scoped size for a read-only compound and vendor lookup server. Each tool covers a necessary function without redundancy or bloat.
The core workflows are covered: find a compound, get its details, see vendor offers, and view vendor trust information. Minor gaps exist, such as no browse-all-compounds endpoint and no individual vendor detail tool, but agents can work around these with the existing tools.