GBrain

Company Brain is an open-source Slack teammate developed by supermemory. It remembers decisions, projects, owners, and other context from the Slack channels and connected tools it can access, answers questions from that information, and can act through tools such as GitHub, Linear, Notion, and Google Workspace via MCP. It can open issues, read pull requests, run repository scripts in a sandbox, return charts, CSVs, and PDFs in Slack, speak up when relevant, and send scheduled digests or perform research. Its memory is organized as a permissions graph: public-channel queries use the shared organizational memory, private-channel queries add that channel's memory, and direct messages can use the asker's personal memory and private channels. Tool writes run through the user's own connection, while access requiring another teammate's connection requires that teammate's approval. The project runs on a user's Cloudflare account using Workers, Durable Objects, D1, KV, and supermemory for memory; it can be deployed through a setup flow or run locally. The repository states that the formerly paid product was discontinued and released under the Apache 2.0 license.

agent-memory is a local-first, agent-agnostic long-term memory runtime for AI agents. It stores memories as plain Markdown files, with a rebuildable SQLite index used as a cache rather than the source of truth. Conversation-boundary hooks trigger writes, while an independent sleep-time Manage pass consolidates, ages, and forgets memories by value; unattended deletion is limited to proposals that require confirmation, and superseded or archived material remains available. The runtime provides three recall paths: deterministic MEMORY.md injection at session start, BM25 search with progressive disclosure, and direct access through the store's directory tree using tools such as ls and grep. Memory records use frontmatter for names, abstracts, status, timestamps, links, weights, and provenance, with free-form Markdown bodies. Its CLI, MCP server, and host-agent hooks share the same validation, hash-diff, and reindexing path, and it can be used by agents that run shell commands, including Claude Code and Codex CLI. The repository documents a Python 3.12-or-later setup using uv, commands for initialization, recording, recall, rebuilding, sleep-time consolidation, and proposal approval, plus host setup for Claude Code and Codex. It does not include an LLM client; reasoning is delegated to the host agent's CLI, so the library requires no separate model keys or billing surface.

Graybox is a local-first long-term memory and personal knowledge-management tool that stores notes as Markdown files with YAML frontmatter. It preserves an immutable inbox of raw captures while an LLM extracts people, projects, tasks, actions, meetings, events, decisions, and other entities into typed, cross-linked pages with backlinks and source citations. Its question-answering function retrieves evidence from captured notes and linked pages and is designed to refuse unsupported answers. Graybox uses keyword search without requiring a vector database, with optional embeddings, and uses LiteLLM to connect to hosted or self-hosted language models. It is distributed as an open-source command-line and terminal user-interface application, with a PyPI package and a GitHub repository.

CowAgent is an open-source AI assistant and agent harness developed by LinkAI. It plans complex tasks step by step, runs tools and skills, controls computers and external services, maintains long-term memory and a personal knowledge base, and supports multi-agent teams with separate roles, models, skills, knowledge, and workspaces. Its architecture routes messages from web and messaging channels through an agent core that reasons over available models, tools, skills, memory, and knowledge before returning a response. Memory uses a three-tier structure of conversation context, daily memory, and long-term MEMORY.md, with a nightly Deep Dream process that distills memories; the knowledge base is an automatically curated Markdown wiki with cross-references and a browsable knowledge graph. Built-in tools include file and terminal operations, web fetching and search, scheduling, memory retrieval, vision, and browser automation, while MCP servers can be added through configuration. Skills can be installed from the Skill Hub, GitHub, ClawHub, or URLs, or authored through conversation. CowAgent supports multiple LLM providers and routes chat, vision, image generation, speech, and embedding workloads separately. It can run locally, in Docker, on a server, or through its macOS and Windows desktop client, with a web console for configuration and a command-line interface for service and skill management. The project is licensed under the MIT License and was formerly named chatgpt-on-wechat.

TencentDB Agent Memory is a self-hostable, team-level memory hub for AI agents. It extracts conversations and tasks into reusable Chat Memory and Skills, and converts documents and code into an LLM Wiki and CodeGraph. These assets can be reviewed, versioned, governed, shared, routed, and reused across agents, frameworks, and team members; existing documents, codebases, and agent sessions can also be imported to reduce cold-start work. The system provides a shared memory server and a proxy that preserves the agent protocol, so supported clients can use the same memory by pointing their base URL at the proxy without plugins, hooks, or an MCP server. The repository deploys memory-core, memory-hub, and the proxy together, with a local management panel and configuration for separate memory and proxy LLM parameters. Documented integrations include DeepSeek Harness, Claude Code, Codex, CodeBuddy, WorkBuddy, Hermes, and OpenClaw.