Agentic Systems: Production-Grade Multi-Agent Infrastructure

Status: 🚧 Alpha | Stack: Python, MCP, ChromaDB, FastAPI

1. Problem Statement

Current LLM agents (Claude, GPT-4, etc.) suffer from catastrophic forgetting:

1. Volatile Context: Closing a VS Code session wipes all working memory.
2. Expensive Re-indexing: Re-sending 50k+ tokens of context costs $1-3 per agent run.
3. No Semantic Querying: Agents cannot answer "What was the database schema decision we made last week?" without re-reading entire conversation history.

This limits agentic systems to single-session tasks and prevents them from acting as true long-term collaborators.

2. Solution Architecture

Agentic Systems provides a local-first, production-grade infrastructure for AI agents:

Current Release: MCP Memory Server v0.1

A Model Context Protocol (MCP) server that gives Claude/GPT persistent, queryable memory.

Key Features:

• 🧠 Semantic Memory: ChromaDB-backed vector storage for automatic fact retrieval
• 🏷️ Metadata Tagging: Categorize memories (architecture, credentials, preferences)
• 🔒 Privacy-First: 100% local execution; no data leaves your machine
• ⚡ Zero-Config: Embedded database; no Docker/Postgres required

Roadmap (Future Modules)

• Agent Control Plane: Distributed state management for multi-agent coordination
• Evaluation Pipeline: CI/CD for agent reliability testing
• Knowledge Graph: Entity relationship mapping for complex queries

3. Quick Start

Prerequisites

• Python 3.10+
• uv (recommended) or pip

Installation

# Clone the repository
git clone https://github.com/prabhuravichandran/agentic-systems.git
cd agentic-systems

# Install dependencies
uv pip install -e .

# Run the MCP server
uv run python src/server.py

Configuration (For Cline/Claude Desktop)

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "memory": {
      "command": "uv",
      "args": ["run", "python", "/path/to/agentic-systems/src/server.py"]
    }
  }
}

Usage Example

# In your Cline chat:
# "Remember that our production database is at 10.0.0.5:5432"
# [Agent calls save_memory tool]

# Later in a different session:
# "What's the production database IP?"
# [Agent calls recall_memory and retrieves the fact]

For comprehensive usage instructions, see docs/usage.md.

Demo

🚧 Interactive Demo Coming Soon

A live demonstration will be available showing:

• Memory persistence across sessions
• Semantic search capabilities
• Integration with Claude Desktop
• Performance benchmarks

4. Architecture

See docs/architecture.md for detailed system design.

graph TD
    Client[Cline / Claude] --"MCP Protocol (stdio)"--> Server[MCP Server Process]
    
    subgraph "Memory Service"
        Server --> Router[Tool Router]
        Router --> Logic[MemoryManager]
        Logic --"Embed Text"--> Embedder[ChromaDB Embeddings]
        Logic --"Store/Query"--> DB[(ChromaDB SQLite)]
    end

5. Contributing

See CONTRIBUTING.md for development guidelines.

6. Changelog

See CHANGELOG.md for version history and release notes.

7. License

MIT License - See LICENSE for details.

Author: Prabhu Ravichandran | LinkedIn | GitHub