NovaMynd
Glama MCP Gateway
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Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.8/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: generating journeys, retrieving assessments, and rendering a UI for tool selection. There is no overlap or ambiguity.
All three tools follow a consistent verb_noun pattern with lowercase and hyphens (generate-journey, retrieve-assessment, tool-selection-interface), ensuring predictability.
With only 3 tools, the set is slightly on the small side but still reasonable for a focused server that combines generation and assessment capabilities. The inclusion of a UI helper tool seems valid.
The server covers generating journeys and retrieving assessments, but lacks tools for listing, updating, or deleting journeys, and does not include a tool for accessing past journey metadata (though a resource is provided). This leaves some lifecycle gaps.
Available Tools
3 toolsgenerate-journeyNeural JourneyAIdempotentInspect
Delivers a personalized neuro-acoustic protocol via Neural Journey based on the user's target performance state and duration. Costs 20 units per generation. After generating, the structured content response contains an "id" field. You can retrieve detailed technical metadata for the journey by reading the resource novamynd://neural-journey/{id}, replacing {id} with the "id" field from the structured content.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The user's target performance state for the journey. Example: "I want to calm down". | |
| duration | Yes | The duration of the journey in minutes. |
Output Schema
| Name | Required | Description |
|---|---|---|
| id | Yes | The journey ID. Use novamynd://neural-journey/{id} to fetch technical metadata. |
| name | Yes | The journey name |
| description | Yes | A summary of the journey experience |
| public_link | Yes | The URL that can be shared publicly |
| management_link | Yes | The URL for managing the journey |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnlyHint, destructiveHint, and idempotentHint. The description adds valuable context: cost (20 units), the response contains an 'id' field, and how to retrieve technical metadata via a resource URI. 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?
Three concise sentences with front-loaded action verb. No unnecessary words; every sentence adds value.
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?
Output schema exists so return values are covered. Description explains the id field and resource retrieval, plus cost. Could be more complete by explaining what 'neuro-acoustic protocol' means, but overall sufficient.
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% for 2 parameters. The description mentions the parameters generically but adds an example for 'prompt'. Baseline 3 is appropriate as schema already documents parameters clearly.
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 function: 'Delivers a personalized neuro-acoustic protocol via Neural Journey based on the user's target performance state and duration.' It distinguishes from siblings like retrieve-assessment and tool-selection-interface by focusing on generation.
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 context about cost and post-generation retrieval, but does not explicitly state when to use this tool versus alternatives or when not to use it. It gives clear usage guidance for after generation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
retrieve-assessmentNeural InsightAIdempotentInspect
Analyzes user intent via Neural Insight to retrieve the most scientifically appropriate cognitive assessment. Maps natural language (e.g., 'I feel drained') to specific cognitive and performance domains like sustained attention, cognitive fatigue, or stress resilience.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | A detailed description of the user's cognitive goal. Example: "Assessing sustained attention due to suspected fatigue". |
Output Schema
| Name | Required | Description |
|---|---|---|
| id | Yes | The assessment ID |
| name | Yes | The assessment name |
| description | Yes | A description about the assessment |
| public_link | Yes | The URL that can be shared publicly |
| management_link | Yes | The URL for managing the assessment |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false) already indicate that the tool may have side effects but is idempotent and safe. The description adds minimal behavioral context beyond 'analyzes' and 'retrieves', which could be interpreted as a read operation despite readOnlyHint=false. This mild ambiguity is not a contradiction, but the description could better align with the annotation or explain side effects.
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 two sentences long, front-loading the main purpose in the first sentence and a clarifying example in the second. Every sentence contributes value without superfluous words.
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 presence of an output schema (not shown but indicated) and only one parameter, the description is largely complete. It covers the tool's function and provides usage context. However, it does not explicitly mention that the output is a structured assessment, which would be useful for completeness but is already handled 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?
Schema coverage is 100%, so the baseline is 3. The description adds context by explaining that the prompt is mapped to cognitive domains, which slightly enhances the schema's description (which already includes an example). However, it does not provide additional syntax, formatting, or constraints beyond what the schema offers.
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 that the tool analyzes user intent via Neural Insight to retrieve a cognitive assessment, specifying the mapping from natural language to domains like sustained attention. It includes a concrete example ('I feel drained') and distinguishes the tool from its siblings (generate-journey, tool-selection-interface) by its explicit focus on cognitive assessment 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 does not provide guidance on when to use this tool versus the sibling tools (generate-journey, tool-selection-interface). It only implies usage when the user describes a cognitive state, but no exclusions or alternative scenarios are mentioned, leaving the agent without sufficient decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tool-selection-interfaceTool Selection InterfaceARead-onlyIdempotentInspect
Renders an MCP app interface for selecting and executing available tools
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description says 'executing available tools' which implies mutation, but annotations declare readOnlyHint=true, creating a contradiction. Beyond annotations, no behavioral context is added.
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?
Single sentence is concise, but could include more context without being verbose.
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?
With no output schema and minimal description, the tool's behavior is under-specified. It doesn't explain the interface's capabilities or what happens after selection.
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?
No parameters exist; schema coverage is 100%. Baseline 4 for zero parameters applies; description adds nothing needed.
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?
Description clearly states it renders an MCP app interface for selecting and executing tools. The verb 'renders' and resource are specific, and it distinguishes from sibling tools like generate-journey and retrieve-assessment.
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?
Description implies usage as a UI for tool selection, but no explicit guidance on when to use versus alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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