A Complete AI Agent Toolkit: Security, Memory, Development, and Context Management

Developers working with AI agents often feel that while agents become more capable, they also become harder to control, with opaque tool usage, mutable logs, and no long‑term memory across sessions.

Four open‑source projects have emerged to tackle these pain points: security, memory, development scaffolding, and context management.

Vigils – Watching Your Agent

Vigils is a locally deployed control panel built with Rust and Tauri. It intercepts every tool call made by an agent and enforces four safeguards:

Audit logs : each tool invocation is recorded and linked with a SHA‑256 hash chain, making logs tamper‑proof.

Approval workflow : dangerous actions such as file writes or network requests pause for user approval, with scopes like “once” or “valid for this session”.

Redaction engine : outgoing prompts are scanned for 13 secret patterns (GitHub PAT, Stripe key, DB connection strings, etc.) and automatically masked; an optional ML model can assist.

Sandbox execution : commands run in an isolated environment; on Linux it uses Landlock to restrict filesystem access.

Vigils also provides a Chrome extension that automatically redacts secrets when pasting content into ChatGPT, Claude, or Gemini pages. curl -fsSL https://vigils.ai/install.sh | sh Then start the service with vigil-hub serve, which creates an MCP gateway that agents must connect through.

GitHub: https://github.com/duncatzat/vigils<br/>Stars: 611 | Language: Rust | License: Apache‑2.0

Memory OS – Letting Agents Remember

Memory OS adds a seven‑layer long‑term memory system to the Hermes Agent, addressing the common issue of agents forgetting context between sessions.

Layer 1 – Workspace : injects a MEMORY.md file into each system prompt.

Layer 2 – Sessions : provides full‑text search over historical dialogues.

Layer 3 – Structured Facts : stores structured facts with trust scores.

Layer 4 – Fabric : enables cross‑session recall using 16 built‑in tools.

Layer 5 – Vector DB : uses Qdrant as the vector store.

Layer 6 – LLM Wiki : automatically curates a knowledge base.

Layer 7 – Ground Truth : marks injected memories as authoritative, preventing the agent from re‑querying external APIs for information it already knows.

The author notes that without Layer 7 the agent often distrusts its own memory, wasting tokens by re‑checking facts.

curl -sSL https://raw.githubusercontent.com/ClaudioDrews/memory-os/main/setup.sh | bash

Requirements: Hermes Agent, Docker, Python 3.11+, and any LLM provider.

GitHub: https://github.com/ClaudioDrews/memory-os<br/>Stars: new project | Language: Python | License: MIT

OpenHands Agent SDK – Scaffold for Building Your Own Agent

OpenHands (formerly OpenDevin) released version 1 of its Agent SDK, a Python + REST API toolkit that lets developers quickly create agents capable of operating code.

from openhands.sdk import LLM, Agent, Conversation, Tool
llm = LLM(model="gpt-5.5", api_key=*** )
agent = Agent(llm=llm, tools=[
    Tool(name="terminal"),
    Tool(name="file_editor"),
    Tool(name="task_tracker"),
])
conversation = Conversation(agent=agent, workspace=os.getcwd())
conversation.send_message("写 3 个事实到 FACTS.txt")
conversation.run()

The SDK runs locally or in Docker/K8s temporary workspaces. Typical use cases include single‑task automation (e.g., generating a README), routine maintenance (updating dependencies), and multi‑agent collaboration (refactoring, code migration). It also supports the MCP protocol, custom tools, and a marketplace of reusable skills.

GitHub: https://github.com/OpenHands/software-agent-sdk<br/>Stars: 802 | Language: Python | License: MIT

Lossless Claw – Preventing Agent “Fragmentation”

Lossless Claw is an OpenClaw plugin that solves the context‑window limitation by organizing conversation history as a directed acyclic graph (DAG). Old messages are summarized into hierarchical nodes; during a dialogue the agent loads the most relevant summaries together with recent messages, staying within token limits without losing information.

Provided tools: lcm<em>grep – search historical messages. lcm</em>describe – view a summary node. lcm_expand – expand a node to see detailed content.

openclaw plugins install @martian-engineering/lossless-claw

After installation the agent automatically manages context, effectively giving it an “always‑remember” capability.

GitHub: https://github.com/Martian-Engineering/lossless-claw<br/>Stars: 4,804 | Language: TypeScript | License: MIT

Together these four projects cover the major pain points of AI agents: Vigils secures tool usage, Memory OS provides reliable long‑term memory, the OpenHands SDK streamlines agent development, and Lossless Claw ensures lossless context handling. They are useful for both power users and developers building new agents.

Reference: the GitHub READMEs of each project.