AI Conversation Logger MCP

中文版 | 日本語版

An intelligent MCP (Model Context Protocol) server designed specifically for AI assistants to automatically log and manage conversation history with developers.

Core Features

• ** AI-Driven Logging** - All content is determined and provided by the AI assistant
• ** Pure Save Mode** - MCP only formats and stores, no content extraction or analysis
• ** Designed for AI Retrospection** - Log format optimized for AI to quickly understand project history
• ** Smart Organization** - Auto-organize by project and date with tagging support
• ** Powerful Search** - Multi-dimensional search by keywords, files, tags, and time range
• ** Context Suggestions** - Smart recommendations based on file associations

Quick Start

1. Install Dependencies

npm install

2. Build Project

npm run build

3. Configure Claude Code

Add MCP server configuration to Claude Code's config file (~/.claude.json):

{
  "mcpServers": {
    "conversation-logger": {
      "command": "node",
      "args": ["/path/to/ai-conversation-logger-mcp/dist/index.js"]
    }
  }
}

4. Restart Claude Code

Restart Claude Code to apply the configuration.

API Tools

1. log_conversation - Core Logging Tool

Records every AI-user interaction with structured information:

interface LogConversationParams {
  userRequest: string;      // User's original request + uploaded file descriptions
  aiTodoList: string[];     // AI's execution plan (list even for view-only tasks)
  aiSummary: string;        // AI's operation summary (3-5 sentences)
  fileOperations?: string[]; // File operations in format: "action filepath - description"
  title?: string;           // Conversation title (optional)
  tags?: string[];          // Tag array (optional)
  project?: string;         // Project name (auto-detected if not provided)
}

2. search_conversations - Search Tool

Search through conversation history with multiple filters:

interface SearchParams {
  keywords?: string[];     // Keyword search
  filePattern?: string;    // File name pattern search
  days?: number;          // Recent N days
  project?: string;       // Project filter (defaults to current)
  tags?: string[];        // Tag filter
  limit?: number;         // Result limit (default: 10)
}

3. get_context_suggestions - Context Recommendations

Get relevant historical context based on current work:

interface ContextParams {
  currentInput: string;    // Current user input
  currentFiles?: string[]; // Currently involved files
  project?: string;        // Project filter (optional)
}

Storage Structure

Logs are stored in the project's ai-logs/ directory:

project-root/
 ai-logs/
    2025-08-07.md     # Daily conversation logs
    2025-08-06.md
    config.json       # Project configuration
 src/
 ...

Log Format

Each conversation is recorded with the following structure:

## [Timestamp] Title #tags

###  User Request
[Original user request]

###  AI Execution Plan
- [x] Completed task
- [ ] Pending task

###  AI Summary
[Summary of what was accomplished]

###  File Operations
- **Created** `path/to/file` - Purpose description
- **Modified** `path/to/file` - What was changed
- **Deleted** `path/to/file` - Reason for deletion

###  Tags
#module #technology #type

Usage Principles

When to Log

All conversations should be logged, including:

• New feature development
• Bug fixes (any size)
• Code refactoring
• Configuration changes
• Code explanations and analysis
• Technical Q&A
• Code reviews
• Any project-related dialogue

Key Points

1. AI-Driven Content - AI determines what information to log
2. Complete Context - Include all relevant details for future reference
3. Focus on "What" not "How" - Emphasize functionality over technical details
4. Consistent Format - Maintain standardized markdown structure

Development

Development Mode

npm run dev

Run Tests

npm test

Code Linting

npm run lint
npm run lint:fix

TypeScript Check

npm run type-check

Technical Stack

• TypeScript - Type-safe development
• MCP SDK - Model Context Protocol implementation
• Node.js - Runtime environment
• Jest - Testing framework

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Contact

For issues or suggestions, please open an issue on GitHub.