brain-mcp and enhanced-mcp-memory

Project B is an enhanced implementation of the Model Context Protocol (MCP) introduced by Project A, making them ecosystem siblings where B expands upon the functionalities and architectural design of the MCP concept from A.

brain-mcp
61
Established
enhanced-mcp-memory
55
Established
Maintenance 13/25
Adoption 14/25
Maturity 18/25
Community 16/25
Maintenance 2/25
Adoption 12/25
Maturity 24/25
Community 17/25
Stars: 25
Forks: 6
Downloads: 818
Commits (30d): 0
Language: Python
License: MIT
Stars: 30
Forks: 8
Downloads: 208
Commits (30d): 0
Language: Python
License: MIT
No risk flags
Stale 6m

About brain-mcp

mordechaipotash/brain-mcp

Your AI has amnesia. Persistent memory and cognitive context for AI. 25 MCP tools. 12ms recall.

Implements a progressive capability model—basic keyword search on raw conversations, semantic search with embeddings, and full domain reconstruction with AI-generated summaries—enabling AI assistants to surface cognitive patterns, unfinished threads, and evolved thinking across fragmented conversation histories from multiple tools (Claude, ChatGPT, Cursor). Operates as an MCP server exposing 25 specialized tools including semantic and keyword search, "prosthetic" functions like `tunnel_state` and `context_recovery` for domain re-entry, and analytics for identifying dormant contexts and thinking trajectories without requiring manual tagging.

About enhanced-mcp-memory

cbunting99/enhanced-mcp-memory

An enhanced MCP (Model Context Protocol) server for intelligent memory and task management, designed for AI assistants and development workflows. Features semantic search, automatic task extraction, knowledge graphs, and comprehensive project management.

Implements a 5-stage sequential thinking engine with token optimization (30-70% compression) and automatic context summarization for conversation continuity, built on FastMCP with SQLite persistence. Automatically detects project conventions (OS, package managers, build tools, runtime types) and learns command patterns to correct AI suggestions—particularly useful for cross-platform development. Exposes 20+ MCP tools including thinking chains, task decomposition, and knowledge graph relationships that link memories to code file paths.

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