MemMCP
A Byzantine fault-tolerant MCP Memory server that uses SQLite write-ahead logging and FAISS hybrid vector search for deterministic, secure memory operations.
README
<div align="center"> <h1>🧠 MemMCP</h1> <p><strong>Deterministic, BFT-Hardened MCP Memory Server for Agent Swarms</strong></p>
<p> <a href="https://github.com/axton/project_2_mcp_memory/actions"><img src="https://img.shields.io/badge/Build-Passing-brightgreen?style=for-the-badge&logo=github" alt="Build Status"></a> <a href="https://python.org"><img src="https://img.shields.io/badge/Python-3.10+-blue?style=for-the-badge&logo=python" alt="Python Version"></a> <a href="https://sqlite.org/index.html"><img src="https://img.shields.io/badge/SQLite-WAL-003B57?style=for-the-badge&logo=sqlite&logoColor=white" alt="SQLite WAL"></a> <a href="https://github.com/axton/project_2_mcp_memory/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-MIT-purple?style=for-the-badge" alt="License"></a> </p> </div>
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MemMCP is a hyper-optimized Memory Server natively implementing the Model Context Protocol (MCP). It bridges the gap between lexical keyword search and semantic vector embeddings, delivering 100% deterministic, deduplicated memory recall for autonomous AI Agent Swarms.
📖 Table of Contents
- Why MemMCP?
- Core Features
- Quick Start
- Architecture
- MCP Tool Reference
- Contributing & Security
- License
🤔 Why MemMCP?
When dozens of autonomous agents operate in parallel, standard vector databases suffer from race conditions, data duplication, and context hallucination. MemMCP solves this by merging SQLite Write-Ahead Logging (WAL) for ACID-compliant state management with FAISS Hybrid Reciprocal Rank Fusion (RRF) for unparalleled semantic retrieval.
✨ Core Features
| Feature | Description | Architecture |
|---|---|---|
| Byzantine Fault Tolerance | Strict isolation of execution states using Bloom-Filter Idempotency tracking. Never stores the same memory twice. | SQLite WAL |
| Data Integrity | Dual-ledger Distributed Consensus architecture powered by Merkle-Root signatures. | msvcrt RWLocks |
| O(N) Vector Batching Bounds | FAISS Semantic search with hybrid RRF logic executing strictly within <50ms latency bounds. |
FAISS + FTS5 |
| Zero-Trust Execution | Hardened against indirect prompt injection with explicit XML RAG bounding. | MCP stdio |
🚀 Quick Start
MemMCP is designed to be booted instantly by any MCP-compliant LLM or Agent Framework via standard IO streams (stdio).
# 1. Clone the repository
git clone https://github.com/axton/project_2_mcp_memory.git
cd project_2_mcp_memory
# 2. Build the exact dependency graph using uv
make build
# 3. Verify the rigorous mathematical test suite
make test
# 4. Boot the MCP server directly
make run
🏗 Architecture
graph TD
A[MCP Client] --> B{Bloom-Filter Idempotency Gate}
B -->|Duplicate Request| C["Drop (Idempotent Return)"]
B -->|New Request| D[Vectorization]
D --> E[FAISS Hybrid RRF Search]
E --> F[SQLite WAL Merkle-Root Ledger]
F --> G[XML RAG Formatter]
G --> H[Response]
🛠 MCP Tool Reference
MemMCP automatically exposes the following functions to any connected agent:
store_memory: Store a single memory. Generates unique keys and updates FAISS indices.store_memories_batch: Store multiple memories atomically in a single massive transaction, rebuilding the index only once.recall_memories: Retrieve relevant memories using Reciprocal Rank Fusion (blending Semantic FAISS similarity + SQLite FTS5 keyword search).
🤝 Contributing & Security
To contribute, you must abide by our strict mathematical isolation limits. See CONTRIBUTING.md for details. For vulnerabilities, refer to SECURITY.md.
📄 License
MIT License. Copyright (c) 2026 Axton Carroll.
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