Skip to main content
Glama
squirrelogic

Feature-Discussion MCP Server

by squirrelogic

provide_feature_input

Submit responses to feature discussion prompts with implementation details and architecture recommendations for software development projects.

Instructions

Provide information for the current feature discussion prompt

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
featureIdYesID of the feature being discussed
responseYesYour response to the current prompt

Implementation Reference

  • Handler for the 'provide_feature_input' tool. Processes user response to current prompt, updates feature discussion data, advances to next prompt or completes discussion, and returns confirmation message.
    case "provide_feature_input": {
      const { featureId, response } = request.params.arguments as any;
      const feature = featureDiscussions[featureId];
      const context = discussionContexts[featureId];
    
      if (!feature) {
        throw new Error(`Feature ${featureId} not found`);
      }
    
      // Find current prompt
      const currentPromptIndex = FEATURE_DISCUSSION_PROMPTS.findIndex(p => p.id === feature.currentPrompt);
      const currentPrompt = FEATURE_DISCUSSION_PROMPTS[currentPromptIndex];
    
      // Store the response
      if (currentPrompt.field === 'requirements' || currentPrompt.field === 'targetUsers' ||
          currentPrompt.field === 'successCriteria' || currentPrompt.field === 'risks') {
        // Handle array fields
        feature[currentPrompt.field] = response.split('\n').map((r: string) => r.trim()).filter(Boolean);
      } else {
        // Handle string fields
        feature[currentPrompt.field] = response;
      }
    
      // Update conversation history
      context.conversationHistory.push({
        prompt: currentPrompt.message,
        response,
        timestamp: new Date().toISOString()
      });
    
      // Move to next prompt if available
      const nextPrompt = FEATURE_DISCUSSION_PROMPTS[currentPromptIndex + 1];
      let responseMessage = "Response recorded. ";
    
      if (nextPrompt) {
        feature.currentPrompt = nextPrompt.id;
        responseMessage += `\n\nNext question:\n${nextPrompt.message}`;
      } else {
        feature.status = 'proposed';
        feature.currentPrompt = undefined;
        responseMessage += "\n\nThank you! The feature has been fully documented. You can now use the 'analyze_feature' or 'suggest_architecture' prompts to get AI guidance on implementation.";
      }
    
      feature.updatedAt = new Date().toISOString();
    
      return {
        content: [{
          type: "text",
          text: responseMessage
        }]
      };
    }
  • src/index.ts:189-207 (registration)
    Tool registration in ListToolsRequestSchema handler, defining name, description, and input schema for 'provide_feature_input'.
      {
        name: "provide_feature_input",
        description: "Provide information for the current feature discussion prompt",
        inputSchema: {
          type: "object",
          properties: {
            featureId: {
              type: "string",
              description: "ID of the feature being discussed"
            },
            response: {
              type: "string",
              description: "Your response to the current prompt"
            }
          },
          required: ["featureId", "response"]
        }
      }
    ]
  • Input schema definition for the 'provide_feature_input' tool, specifying required parameters: featureId and response.
    inputSchema: {
      type: "object",
      properties: {
        featureId: {
          type: "string",
          description: "ID of the feature being discussed"
        },
        response: {
          type: "string",
          description: "Your response to the current prompt"
        }
      },
      required: ["featureId", "response"]
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'provide information', which suggests a read or input operation, but doesn't clarify if this is a mutation, requires specific permissions, has side effects, or details the response format. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and appropriately sized for its function, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns, how it interacts with the sibling tool 'begin_feature_discussion', or provide behavioral details. For a tool with two required parameters and no structured support, the description should offer more context to guide the agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with clear descriptions for both parameters ('featureId' and 'response'). The description adds no additional meaning beyond what the schema provides, such as explaining the context or format of 'response'. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose as 'Provide information for the current feature discussion prompt', which is clear but vague. It specifies the action ('provide information') and context ('current feature discussion prompt'), but doesn't clarify what type of information or how it differs from the sibling tool 'begin_feature_discussion'. This makes it adequate but with room for improvement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as the sibling tool 'begin_feature_discussion'. It implies usage in the context of a 'current feature discussion prompt', but lacks explicit instructions on prerequisites, timing, or comparisons to other tools, leaving the agent with minimal direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/squirrelogic/mcp-feature-discussion'

If you have feedback or need assistance with the MCP directory API, please join our Discord server