shared-memory-mcp

mcp
Security Audit
Warn
Health Warn
  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 7 GitHub stars
Code Pass
  • Code scan — Scanned 11 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This server provides a shared memory system for coordinating multiple AI agents working together on a single task. It stores shared context, manages work distribution, and allows agents to share discoveries efficiently without duplicating data.

Security Assessment
Overall risk: Low. The codebase scan across 11 files found no dangerous patterns, hardcoded secrets, or requests for risky permissions. The tool is designed to handle local workspace logic, task distribution, and text summarization rather than interacting with external networks. There is no indication that it executes arbitrary shell commands. However, because the repository has very low community visibility, a manual review of the full source code is recommended before exposing it to highly sensitive environments.

Quality Assessment
The project is actively maintained, with its most recent code push occurring today. It uses a standard, permissive MIT license and includes clear installation and usage instructions. The main concern is its extremely low community adoption, sitting at only 7 GitHub stars. This means the project has not been widely battle-tested by the developer community, which typically indicates a higher risk of undiscovered bugs or abandoned future updates.

Verdict
Use with caution: the code appears clean and actively maintained, but the lack of community adoption means it should be tested in isolated environments before relying on it for critical workflows.
SUMMARY

Shared Memory MCP server for agentic teams - solving coordination tax with 6x token efficiency

README.md

Shared Memory MCP Server

Solving coordination tax in agentic teams - where Opus + 4 Sonnets burns 15x tokens but only gets 1.9x performance.

Prerequisites

  • Node.js 18+
  • npm or yarn
  • Claude Desktop (for MCP integration)

The Problem

Current agentic team patterns have terrible token efficiency:

  • Traditional: 1 request × 4K tokens = 4K tokens
  • Agentic Team: 1 coordinator + 4 workers × 12K tokens each = 48K+ tokens
  • Efficiency: 1.9x performance / 15x cost = 12% efficiency

This MCP server provides shared memory for agentic teams to achieve 6x token efficiency while maintaining coordination benefits.

Core Features

1. Context Deduplication

  • Store shared context once, reference by key
  • 10:1 compression ratio with intelligent summarization
  • Workers get 100-token summaries instead of full context

2. Incremental State Sharing

  • Append-only discovery system
  • Workers share findings in real-time
  • Delta updates prevent retransmission

3. Work Coordination

  • Claim-based work distribution
  • Dependency tracking and resolution
  • Reactive task handoff between workers

4. Token Efficiency

  • Context compression and lazy loading
  • Delta updates since last version
  • Expansion on demand for specific sections

Installation

# Clone the repository
git clone https://github.com/haasonsaas/shared-memory-mcp.git
cd shared-memory-mcp

# Install dependencies
npm install

# Build the server
npm run build

Quick Start

# Run in development mode
npm run dev

# Or run the built server
npm start

# Test the agentic workflow
npm test
# or
npm run test-workflow

Usage Example

// 1. Create agentic session (coordinator)
const session = await mcp.callTool('create_agentic_session', {
  coordinator_id: 'opus-coordinator-1',
  worker_ids: ['sonnet-1', 'sonnet-2', 'sonnet-3', 'sonnet-4'],
  task_description: 'Analyze large codebase for performance issues',
  codebase_files: [...], // Full context stored once
  requirements: [...],
  constraints: [...]
});

// 2. Workers get compressed context (not full retransmission)
const context = await mcp.callTool('get_worker_context', {
  session_id: session.session_id,
  worker_id: 'sonnet-1'
}); // Returns summary + reference, not full context

// 3. Publish work units for coordination
await mcp.callTool('publish_work_units', {
  session_id: session.session_id,
  work_units: [
    { unit_id: 'analyze-auth', type: 'security', priority: 'high' },
    { unit_id: 'optimize-db', type: 'performance', dependencies: ['analyze-auth'] }
  ]
});

// 4. Workers claim and execute
await mcp.callTool('claim_work_unit', {
  session_id: session.session_id,
  unit_id: 'analyze-auth',
  worker_id: 'sonnet-1',
  estimated_duration_minutes: 15
});

// 5. Share discoveries incrementally
await mcp.callTool('add_discovery', {
  session_id: session.session_id,
  worker_id: 'sonnet-1', 
  discovery_type: 'vulnerability_found',
  data: { vulnerability: 'SQL injection in auth module' },
  affects_workers: ['sonnet-2'] // Notify relevant workers
});

// 6. Get only new updates (delta, not full context)
const delta = await mcp.callTool('get_context_delta', {
  session_id: session.session_id,
  worker_id: 'sonnet-2',
  since_version: 5 // Only get changes since version 5
});

Architecture

┌─────────────────┐    ┌─────────────────┐
│ Opus Coordinator│    │ Shared Memory   │
│                 │────│ MCP Server      │
│ - Task Planning │    │                 │
│ - Work Units    │    │ - Context Store │
│ - Coordination  │    │ - Discovery Log │
└─────────────────┘    │ - Work Queue    │
                       │ - Dependencies  │
┌─────────────────┐    └─────────────────┘
│ Sonnet Workers  │           │
│                 │───────────┘
│ - Specialized   │    
│ - Parallel      │    ┌─────────────────┐
│ - Coordinated   │    │ Token Efficiency│
└─────────────────┘    │                 │
                       │ 48K → 8K tokens │
                       │ 6x improvement  │
                       │ 1200% better ROI│
                       └─────────────────┘

Token Efficiency Strategies

Context Compression

// Instead of sending full context (12K tokens):
{
  full_context: { /* massive object */ }
}

// Send compressed reference (100 tokens):
{
  summary: "Task: Analyze TypeScript codebase...",
  reference_key: "ctx_123", 
  expansion_hints: ["codebase_files", "requirements"]
}

Delta Updates

// Instead of retransmitting everything:
get_full_context() // 12K tokens each time

// Send only changes:
get_context_delta(since_version: 5) // 200 tokens

Lazy Loading

// Workers request details only when needed:
expand_context_section("codebase_files") // 2K tokens
request_detail("file_content", "auth.ts") // 500 tokens

API Reference

Session Management

  • create_agentic_session - Initialize coordinator + workers
  • get_session_info - Get session details
  • update_session_status - Update session state

Context Management

  • get_worker_context - Get compressed context for worker
  • expand_context_section - Get detailed section data
  • get_context_delta - Get incremental updates

Work Coordination

  • publish_work_units - Publish available work
  • claim_work_unit - Claim work for execution
  • update_work_status - Update work progress

Discovery Sharing

  • add_discovery - Share findings with team
  • get_discoveries_since - Get recent discoveries

Dependency Resolution

  • declare_outputs - Declare future outputs
  • await_dependency - Wait for dependency
  • publish_output - Publish output for others

MCP Configuration

For Claude Desktop

  1. Copy the example configuration:

    cp claude-desktop-config.example.json claude-desktop-config.json
    
  2. Edit claude-desktop-config.json and update the path to your installation:

    {
      "mcpServers": {
        "shared-memory": {
          "command": "node",
          "args": ["/absolute/path/to/shared-memory-mcp/dist/server.js"]
        }
      }
    }
    
  3. Add this configuration to your Claude Desktop config file:

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
    • Linux: ~/.config/Claude/claude_desktop_config.json

Note: The claude-desktop-config.json file is gitignored as it contains machine-specific paths.

Performance Benefits

Metric Traditional Agentic (Current) Shared Memory MCP
Token Usage 4K 48K+ 8K
Performance Gain 1x 1.9x 1.9x
Cost Efficiency 100% 12% 1200%
Coordination None Poor Excellent

License

MIT

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