Physician-reviewed medical opinions and prescriptions for AI agents.
List all conditions and medications available through Appendix
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Filter by category name (case-insensitive, e.g. 'respiratory') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds minimal extra context ('available through Appendix') but doesn't elaborate on behavioral implications like page limits or data freshness. No contradiction.
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, front-loaded sentence with no wasted words. Every part (verb, resource, scope) is necessary and immediately informative.
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 list tool with one optional parameter, the description is mostly complete. However, it omits what 'Appendix' refers to and whether the output includes both conditions and medications as implied by the title. Still, annotations provide missing behavioral safety.
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%, and the schema already describes the 'category' parameter with case-insensitivity and an example. The tool description adds no additional meaning beyond what the schema provides.
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 action ('List') and the resource ('all conditions and medications available through Appendix'). It distinguishes from sibling tools: 'search_knowledge_base' implies searching, not listing all, and 'submit_encounter' is a write operation.
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?
No guidance on when to use this tool versus alternatives, such as 'search_knowledge_base'. Lacks mention of prerequisites or context where listing all is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search Appendix's medical knowledge base for clinical literature, treatment guidelines, and reference material to help the user describe their medical issue
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results to return (1-10, default 5) | |
| query | Yes | Search query (clinical topic or question) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description carries less burden. It does not contradict annotations, but it adds only general context (types of material) without detailing behavior like result structure, pagination, or ranking. Thus, adequate but not enriching.
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 efficiently conveys the action and purpose. It is front-loaded with the key action and resource. Slight room for trimming but overall concise and 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 search tool with two parameters and no output schema, the description provides adequate context (resource and purpose). However, it lacks details on result format or how to interpret output, which could be important for an agent. Sibling tools are not referenced, leaving some ambiguity.
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%, with both parameters well-described in the input schema (query and limit). The description adds no additional meaning beyond what the schema provides, so the baseline score of 3 is appropriate.
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 verb 'Search' and the specific resource 'Appendix's medical knowledge base', listing content types (clinical literature, treatment guidelines, reference material). It distinguishes from siblings by focusing on medical literature search, while list_conditions and submit_encounter imply different operations.
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 use when helping a user describe a medical issue, but it does not explicitly state when to use this tool versus alternatives like list_conditions or submit_encounter. No exclusions or when-not conditions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Submit a clinical encounter letter to the Appendix physician team for review. The letter should be in Markdown format following the Appendix letter structure. Returns feedback on completeness or a checkout URL when ready. One of our board-certified physicians will personally review the submission and provide clinical guidance and a prescription if appropriate.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Clinical letter in Markdown format (500-10,000 characters) | |
| images | No | Up to 3 images to attach | |
| session_token | No | Token from a previous response to continue the same encounter |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=false and destructiveHint=false, which the description supports by indicating a non-destructive write operation. The description adds meaningful behavioral context: the submission undergoes human review by a physician, implying asynchronous handling and potential time delay. This goes beyond what annotations convey.
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: main action, return behavior, and additional context about physician review. It is front-loaded and contains no redundant 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?
Given the tool has three parameters well-documented in the schema and no output schema, the description covers the essential workflow, return types, and human involvement. However, it does not specify the conditions for returning feedback versus a checkout URL, nor the expected timeframes, which could be useful.
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% with all three parameters described. The description adds value beyond the schema by specifying the required format ('Markdown following the Appendix letter structure') and implicitly clarifying the role of session_token (continuation context). This assists in correct parameter usage.
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 uses specific verb 'Submit' and resource 'clinical encounter letter to the Appendix physician team'. It clearly distinguishes from siblings 'list_conditions' and 'search_knowledge_base', which are unrelated operations.
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 states when to use: to submit a clinical letter for physician review. It implies the tool is for one specific workflow and provides context about outcomes (feedback or checkout URL). While no explicit 'when not to use' is given, sibling tools are sufficiently different to avoid confusion.
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.
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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Expert review for AI agents. On-chain proof of human review.
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Doctor-reviewed blood-test markers, conditions & symptoms as agent tools. EN/RU/HE. Hosted.
Real licensed Kenyan doctors, pharmacy and groceries. AI discovery only, payment held in escrow.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: listing conditions, searching knowledge base, and submitting encounters. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern using snake_case (list_conditions, search_knowledge_base, submit_encounter).
Three tools is on the smaller side but appropriate for the focused domain of medical reference and encounter submission. Each tool serves a clear function.
The core workflow (list conditions, search, submit) is covered, but missing operations like retrieving encounter history or managing submitted encounters would aid completeness.
