Feature-Discussion MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| begin_feature_discussionC | Start a new feature discussion |
| provide_feature_inputC | Provide information for the current feature discussion prompt |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| analyze_feature | Get AI analysis and recommendations for a feature |
| suggest_architecture | Get architectural recommendations for a feature |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: 'begin_feature_discussion' initiates a new discussion, while 'provide_feature_input' adds information to an existing one. There is no overlap in functionality, making it impossible for an agent to confuse them.
Both tools follow a consistent verb_noun pattern with snake_case naming. 'begin_feature_discussion' and 'provide_feature_input' use clear, descriptive verbs ('begin' and 'provide') paired with the same noun phrase ('feature_discussion' or 'feature_input'), ensuring predictability.
With only 2 tools, the server feels thin for a feature discussion domain. It lacks essential operations like retrieving, updating, or closing discussions, which limits its utility and suggests an incomplete scope.
The tool surface is severely incomplete for feature discussions. It covers starting a discussion and providing input, but missing critical operations such as getting discussion details, listing discussions, updating status, or adding comments, which will likely cause agent failures in real workflows.