"ACM" matching MCP servers:

Provides a local-first, provenance-aware memory layer that enables MCP-capable AIs to store, recall, validate, and reason over facts with contradiction detection, trust weighting, deduplication, and encryption, supporting offline private operation without GPUs or API keys.

Enables lossless context management for OpenAI Codex CLI by capturing and compressing conversation history in SQLite, with lexical recall via MCP tools.

Exposes the 7-prime spine, 7 κ-bands, and 6 fold operations as native tools and resources for any MCP client, enabling foldkit-based state folding, band classification, and origami-inspired operations.

Implements Agentic Context Engineering to create self-improving AI coding assistants that learn from execution feedback and build persistent knowledge playbooks. Reduces token usage by 86.9% while improving code accuracy by 10.6% through incremental context updates.

Persistent memory for Claude Code — a self-evolving knowledge layer that survives across sessions, grows from every conversation, and surfaces relevant context automatically.

Enables coding agents to govern and access memory engines over MCP, with scoped read/write permissions, journaling, secret scrubbing, and bounded context delivery at session start.

Serves project memory, tasks, docs, and conventions live over the Model Context Protocol, enabling AI assistants to query and manipulate workspace context directly. Exposes tools for task management, memory operations, search, and context health checks.

MCP server for Agent Context OS that compiles engineering docs into a knowledge graph, detects code drift, and serves token-budgeted context packs to AI coding agents via MCP.

This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.

Exposes ACR's memory, skill, web, and GitHub search tools to any MCP client, enabling task execution and tool access via the MCP protocol.

Provides structured external memory for AI assistants, enabling persistent context, branch notes, tacit knowledge, and checklists to overcome AI memory loss and context confusion.

An encrypted, local-first memory server for AI agents that uses SQLite + FTS5 hybrid search, keeping memory off the GPU to maximize HBM for inference.

This MCP server enables AI agents to manage artifacts across sessions by providing tools for searching, retrieving, and registering entries in a persistent ledger, ensuring consistency and traceability of agent outputs.

MCP server that provides semantic search, graph query, and keyword search tools for interacting with DocSmith's knowledge graph and documentation.

Interaction profile registry for AI agents. Log interactions to build a behavioral profile, query it through lenses: friction, coverage, stable corridors, failure registry, and trend. 21 tools.

Enables automatic memory retrieval and injection for AI conversations to provide continuous learning through semantic search and memory management.

MCP server for indexing source code from repositories into a Neo4j graph database and enabling Graph RAG-based search and traversal of functions via natural language queries.

A cognitive memory system for MCP that provides hybrid retrieval, memory layers, entity graph, and 83 tools for recall, remember, codebase scanning, and more.