Neural memory

from drakonkat

A memory for AI, without cloud service or fee, everything local (Most useful for coding)

🔥🔥✓ VerifiedFreeQuick setup

🧠 Neural Memory v2.0

⚠️ IMPORTANT NOTICE: This is an experimental MCP (Model Context Protocol) tool. While it has shown promising results when used locally, it is still under active development and may evolve over time. Feedback and contributions are highly appreciated! Please report any issues, suggestions, or feature requests on our GitHub Issues page. Your input helps make this tool better for everyone! nya~

Model Context Protocol (MCP) system for knowledge memorization and contextual retrieval.

🚀 Try Neural Memory NOW!

Want to try it right away in your Cline? Add this configuration to your cline_mcp_settings.json:

{
  "mcpServers": {
    "neural-memory": {
      "timeout": 120,
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@drakonkat/neural-memory@latest"
      ]
    }
  }
}

For Local Development

{
  "mcpServers": {
    "neural-memory": {
      "timeout": 120,
      "type": "stdio",
      "command": "node",
      "args": [
        "./neural-memory/src/index.js"
      ]
    }
  }
}

⚠️ Note: Replace the path with your local project path!

What's New in v2.0

🎯 Unified Database

No more separate databases per project! All memory resides in a single SQLite database
Faster, simpler, zero configuration

🎓 Skills Framework

Rigid schema for registering skills with consistent structure
framework, language, filePattern, learnSteps, useCases
Automatic context-based suggestions

📊 HTML Reports

Generate visual reports of your memory
Statistics, most used skills, recent work

Available Tools

Node Management

Tool	Description
`add_node`	Add node to memory
`search_nodes`	Search nodes (with FTS5 + confidence)
`delete_node`	Delete node

Skills Framework

Tool	Description
`register_skill`	Register skill (rigid schema)
`suggest_skills`	Suggest skills

Context Management

Tool	Description
`save_context_snapshot`	Save context snapshot
`restore_context`	Restore context

Reports

Tool	Description
`get_memory_report`	JSON/HTML report

Node Types

Type	Priority	Use Case
`skill`	⭐⭐⭐	Knowledge skill
`error`	⭐⭐⭐	Resolved error
`operation`	⭐⭐	How-to
`convention`	⭐⭐	Naming rules
`edge_case`	⭐⭐	Edge case
`pattern`	⭐	Design pattern
`task`	⭐	Completed task
`generic`	⭐	Generic node

Confidence Scoring

The system calculates a confidence score (0.0-1.0) for each result based on:

BM25 Score (35%) - Full-text search ranking
Keyword Match (25%) - Keywords overlap
Recency Bonus (10%) - Recent nodes preferred
Type Score (15%) - Skills/errors are more important
Weight (15%) - Manual weight

Rigid Skill Schema

{
  "name": "Skill Name",
  "framework": "fastify|react|prisma|...",
  "language": "javascript|typescript|python|...",
  "filePattern": "**/*.service.js",
  "learnSteps": ["Step 1", "Step 2"],
  "useCases": ["Case 1", "Case 2"],
  "implementation": "// Code...",
  "examples": ["file1.js"],
  "prerequisites": ["Prerequisite 1"]
}

Database

The unified database is located at:

data/neural-memory-unified.sqlite

License

MIT

Copy & paste — that's it

npm install neural-memory

Quick Start

import { initialize, handleMcpRequest } from 'neural-memory';

// Initialize the service
await initialize();

// Add a node
await handleMcpRequest('add_node', {
  keywords: ['fastify', 'middleware', 'auth'],
  content: 'Implementation of JWT middleware...',
  type: 'generic'
});

// Register a skill
await handleMcpRequest('register_skill', {
  name: 'Fastify CRUD API',
  framework: 'fastify',
  language: 'javascript',
  filePattern: '**/*.service.js',
  learnSteps: [
    '1. Initialize project',
    '2. Create validation schema',
    '3. Implement handler'
  ],
  useCases: [
    'Create REST API',
    'Handle standardized errors'
  ]
});

// Search for skills
const skills = await handleMcpRequest('suggest_skills', {
  currentKeywords: ['fastify', 'api'],
  domain: 'javascript'
});

// Save context
await handleMcpRequest('save_context_snapshot', {
  summary: 'Refactoring 80% complete',
  pendingTasks: ['Integration testing', 'Deploy to staging'],
  learnings: ['Prisma requires explicit migrations']
});

// Generate report
const report = await handleMcpRequest('get_memory_report', {
  format: 'html'
});

Installation

npm install neural-memory