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OpenViking

Appears in 7 awesome lists

ByteDance's context database for AI agents that unifies memory, resources, and skills through a filesystem paradigm, enabling hierarchical context delivery where agents pull only the paths they need instead of receiving bloated monolithic prompts. The self-evolving layer that restructures context…

Open github.comvolcengine/openviking

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Awesome DeepSeek Harness

Section: Memory & Knowledge · OpenViking memory/context plugin for DeepSeek Harness: connects dsh to OpenViking's self-evolving context database for cross-session agent memory and knowledge RAG.

FreshScore 84

Awesome Harness Engineering

Section: Context Delivery & Compaction · ByteDance's context database for AI agents that unifies memory, resources, and skills through a filesystem paradigm, enabling hierarchical context delivery where agents pull only the paths they need instead of receiving bloated monolithic prompts. The self-evolving layer that restructures context…

FreshScore 88

awesome-jev

Section: Scoring & Ranking · Reranking: Volcengine's agent context database ships a Jev rerank client that scores each candidate document with jev-latest against api.typesafe.ai and treats the returned probability as relevance, because TypeSafe exposes no native rerank endpoint.

FreshScore 83

Awesome Open Source AI

Section: 4. Agentic AI & Multi-Agent Systems · Open-source context database for AI agents that unifies agent memory, knowledge RAG, and skills as a virtual filesystem. AGPL 3.0 licensed.

FreshScore 89

Awesome Python

Section: AI and Agents · A context database for AI agents that unifies memory, resources, and skills.

FreshScore 94

Indie Hacker Tools Plus

Section: 数据库与存储 (Database & Vector) · 上下文数据库。火山引擎开源,专为 Agent 长期记忆与分层上下文管理设计。

FreshScore 86

awesome-python

Section: Other · Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.

FreshScore 81

Context7

MCP server and CLI that injects up-to-date, version-specific library documentation directly into agent context, eliminating hallucinated APIs and outdated code examples caused by stale training data. Ships as both a ctx7 command-line tool and an MCP server with resolve-library-id and query-docs…

In 6 listsDetails

Effective Context Engineering for AI Agents

Anthropic's systematic guide to managing the full context state—system prompts, tools, MCP, and message history—as a finite, curated resource. Reframes harness design as "what configuration of context produces the desired behavior?" rather than just prompt wording.

In 5 listsDetails

codebase-memory-mcp

High-performance code intelligence MCP server that full-indexes repositories into a persistent knowledge graph via tree-sitter AST analysis across 66 languages. Replaces dozens of file-read/grep cycles with sub-millisecond structured queries, cutting active tokens by 120× and turning codebase…

In 5 listsDetails

Supercov

[supercov] - Code quality and test coverage for coding agents: Jev scores each source file so the agent knows what to fix first

In 4 listsDetails

Harness Engineering

OpenAI's framing of harness engineering as a discipline: how to design the scaffolding that lets Codex and similar agents operate reliably in an agent-first world.

In 4 listsDetails

google-labs-code/design.md

DESIGN.md是一套专为AI编程代理设计的视觉标识描述规范,它通过提供持久且结构化的设计系统上下文,精准解决了大语言模型在自动化生成代码时因缺乏统一设计规范而导致的界面风格漂移与重复沟通痛点。该项目相较于传统工具的核心优势在于其标准化架构能够彻底消除多智能体协作中的认知碎片化,凭借内置的层级化索引机制实现设计规则的长期记忆而非短暂会话存储,同时依托原生Markdown语法实现了无需额外解析器的无缝工程集成,从而在易用性与稳定性上显著优于依赖私有格式的竞品方案。在底层运作逻辑上,该规范犹如为编程代理配备了一本可随时查阅的“数字化建筑蓝图”,它将抽象的色彩、字体与组件规范转化为带标题层级的树…

In 4 listsDetails

headroom

Compresses tool outputs, logs, files, and RAG chunks before they enter the context window, cutting active tokens by 60–95% without changing answers. Ships as a library, proxy, and MCP server — the right drop-in layer for any harness where bulky tool returns are the primary context pressure source.

In 4 listsDetails

Mirage

Swaps the filesystem and bash providers for a mirage virtual workspace: file tools and shell commands run over mounted resources (RAM, S3, Redis, Slack, Gmail, Notion, Postgres) instead of the host disk, with per-mount read/write/exec modes, per-command sandbox routing (monty, pyodide, quickjs in…

In 3 lists