SDOF Knowledge Base

# SDOF Knowledge Base MCP Server Usage Guide This document provides detailed instructions on how to use the SDOF Knowledge Base MCP server with Roo Code. ## Configuration To use this MCP server with Roo, add the following configuration to your MCP settings: ```json { "mcpServers": { "sdof_knowledge_base": { "command": "cd", "args": ["C:\\Users\\thegr\\integration-main\\integration\\sdof_knowledge_base", "&&", "npm", "start"], "disabled": false } } } ``` > Note: Adjust the path to match your actual installation directory. ## Available Tools ### store_sdof_plan Stores an SDOF plan in both the filesystem and knowledge base. #### Input Schema ```json { "plan_content": "The full markdown content of the SDOF plan", "metadata": { "planTitle": "Title of the plan", "planType": "exploration|analysis|implementation|evaluation|integration|synthesis", "tags": ["tag1", "tag2", "tag3"] } } ``` | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | plan_content | string | Yes | The full markdown content of the SDOF plan | | metadata | object | No | Additional metadata about the plan | | metadata.planTitle | string | No | Title of the plan (default: "SDOF Plan {timestamp}") | | metadata.planType | string | No | Type of the plan (default: "misc") | | metadata.tags | string[] | No | Array of tags for categorization (default: []) | #### Example Usage From the SDOF Orchestrator or any other Roo mode, you can use the tool as follows: ```xml <use_mcp_tool> <server_name>sdof_knowledge_base</server_name> <tool_name>store_sdof_plan</tool_name> <arguments> { "plan_content": "# Phase 1: Exploration Results\n\n## Problem Statement\n\nThe problem is to design...\n\n## Approaches\n\n### Approach 1\n...", "metadata": { "planTitle": "Exploration: Designing a Vector Database", "planType": "exploration", "tags": ["vector-db", "semantic-search", "embeddings"] } } </arguments> </use_mcp_tool> ``` #### Response Format Upon successful execution, the tool returns: ```json { "message": "Plan stored successfully.", "filePath": "docs/plans/explorations/2025-04-09-exploration-designing-a-vector-database.md", "entryId": "64e8a7b2c3d5f4a1e2b3c4d5" } ``` ## Integration with SDOF Workflow ### Automatic Plan Storage After each SDOF phase completes, you can add the following code to your SDOF Orchestrator to automatically save the plan: ```javascript // Example: After Phase 1 (Exploration) const explorationResults = await sdofExplorer.completeTask(); // Store the results in the knowledge base await useMcpTool({ serverName: "sdof_knowledge_base", toolName: "store_sdof_plan", arguments: { plan_content: explorationResults.markdown, metadata: { planTitle: `Exploration: ${problemStatement.substring(0, 50)}...`, planType: "exploration", tags: ["sdof", "phase1", ...domainTags] } } }); ``` ### Retrieving Past Solutions In future versions, additional tools will be added to retrieve relevant past solutions based on the current problem, enabling the SDOF workflow to learn from past experiences. ## File Organization Plans are automatically saved to the filesystem in the following directory structure: ``` docs/ └── plans/ ├── explorations/ # Phase 1 plans ├── analyses/ # Phase 2 plans ├── implementations/ # Phase 3 plans ├── evaluations/ # Phase 4 plans ├── integrations/ # Phase 5 plans ├── syntheses/ # Final synthesis plans └── misc/ # Other plans ``` Each file is named using the format: `YYYY-MM-DD-plan-title.md`