MCP server that gives AI coding agents persistent memory about your codebase
Storage, memory and knowledge management for agents.
MCP server that gives AI coding agents persistent memory about your codebase
Self-hosted AI memory ledger. You and your agents share one memory store over MCP — one SQLite file, web UI, REST, works offline.
prom.codes Memory — persistent, local-first agent memory as an MCP server.
MCP server for systematic thinking, mental models, debugging approaches, and memory management
DSH plugin that bridges the local codebase-memory-mcp knowledge-graph server through the built-in @deepseek-ai/dsh-mcp-client, with a runtime-configurable exe path (settings namespace).
AI-powered changelog generator with MCP server support - works with most providers, online and local models
Read-only local MCP server for explaining Microsoft Intune assignments.
Trace any user action from the UI to the database. Maps every click through React/Next.js, NestJS/Express, Prisma, Mongoose and the MongoDB driver, flowcharts its decisions, explains the database schema in plain words, shows what a change breaks, finds de
Memory and workflow automation for MCP, Codex, and Claude Code. Reuse repeatable developer operations through skills and explicit feedback.
Family meal planning run by your own AI agent: weekly dinners, household votes, grocery list minus the pantry. Stdio MCP server for the hosted Agent Chef service (https://agentchef.net/mcp).
Reduce Claude Code token usage by 70-90% with cross-session memory and four-layer optimization: semantic codebase indexing, PostToolUse tool compression, turn summarization, and session consolidation. MCP server powered by Ollama — zero API calls, runs en
PMLL Memory MCP — persistent KV context memory and Q-promise deduplication.
MCP server for ExoVault — read, search, and manage encrypted notes from Claude Code
A Model Context Protocol server for persistent project-specific AI agent context.
A Model Context Protocol (MCP) server for ATLAS, a Neo4j-powered task management system for LLM Agents - implementing a three-tier architecture (Projects, Tasks, Knowledge) to manage complex workflows.
Self-hosted shared memory for a team of AI agents. Rooms, L0-L3 depth, no LLM on the read path.
Universal RAG Memory MCP Server for AI assistants
Structured thinking + steel-manning verification for AI agents. Backed by 43+ papers.
Universal AI Agent Skills: Docker 3-Tier Workflow, Enterprise Production Architecture (NGINX, Cloudflare, Log Rotation), Git Team Workflow, AI API Gateway (9Router & LLM Routing), Oracle External Brain Lifecycle (~/ψ Vault), and Maymint Companion Soul & M
LatentContext MCP Server: session-isolated memory, a knowledge graph, a live code index with call graphs, and stateful code review for MCP hosts