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Memory MCP Server

Persistent knowledge graph for LLM workflows

AWSKnowledge GraphMCPServerless

A cloud-based persistent memory system that gives AI coding assistants long-term memory across sessions, devices, and projects. Built on AWS serverless infrastructure with semantic search powered by Bedrock embeddings.

Production — AWS serverless Source

Features

Knowledge graph storage

Single-table DynamoDB design with adjacency list pattern. Stores entities (projects, decisions, bugs, concepts, people) and their relationships in one table.

Semantic search

Bedrock Titan Embed V2 generates 256-dim vectors stored alongside entities. Natural-language queries find relevant knowledge via cosine similarity.

Session tracking

Chronological session records — what was done, what was decided, which entities were involved. Filter by project, sorted newest-first.

MCP tools

Six tools via MCP: memory_write, memory_search, memory_graph_query, memory_list_sessions, memory_get_session, memory_get_context. Plug into any MCP client.

S3 document archive

Every entity backed up as human-readable Markdown in S3. Browse your knowledge base as files, or use it as a future Bedrock Knowledge Base source.

Architecture

API Gateway → Lambda (FastMCP + Mangum) → DynamoDB (entities + sessions) + S3 (markdown archive) + Bedrock (embeddings). Fully serverless, pay-per-request.

Tech Stack

Python FastMCP AWS Lambda DynamoDB S3 Bedrock Titan API Gateway SAM