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knaisoma/data-olympus

knaisoma/data-olympus

Git-native Markdown knowledge
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add data-olympus -- npx -y data-olympus
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
30 ★ · knaisoma/data-olympus · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 30 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 knaisoma/data-olympus;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

data-olympus

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**New here? Start with WHY.md.** It is the story behind the project: the
problem we kept hitting with coding agents, what data-olympus does differently, how
it relates to Google's Open Knowledge Format, and where our benchmarks say it is
strong and where it is not. The rest of this README is the technical reference.
data-olympus is a governance-grade knowledge-base format and server for agent workforces. It is readable by Open Knowledge Format (OKF) v0.2 consumers: it inherits OKF's directory structure, frontmatter conventions, reserved filenames, and link model, then layers governance extensions on top (stable id, controlled type/status/tier fields, supersedes chains) plus a single-writer MCP server and a CLI. CI proves two concrete directions against official Google OKF v0.2 commit ad30107c31c06aec8a7d5636e0d1058118604e6f: its reference visualization consumer reads every concept in example-bundle, and data-olympus imports, lints, indexes, searches, and retrieves the pinned official Bitcoin sample. This is fixture-scoped interoperability evidence, not a blanket guarantee for every OKF bundle or future upstream revision. The result is a git-native, version-controlled document graph of engineering standards, architectural decisions, and project knowledge that agents and humans can read, search, and extend without any proprietary service.
It governs *decisions*, not code. When an agent is about to make a choice (a library, a pattern, a migration), data-olympus surfaces the established standard or decision that should govern that choice. It is deliberately **not** a code-search, reference-finding, or "where is X used" tool: LSP, grep, and Sourcegraph already do that well. The retrieval task it targets is coding-intent to governing-rule, and it helps where current model interaction during vibe-coding is weakest: keeping the model aligned to patterns the team has already established as correct.
**Status: pre-1.0 beta. Stable releases are distributed through PyPI and GHCR.**
Why
- **Portable, no lock-in.** The entire KB is a directory of markdown files in git. No database, no proprietary schema, no vendor.
- **Git-native diffs and review.** Every change is a commit. Proposed edits go through a pending queue before commit; history is plain git log.
- **Agent and human readable.** Plain markdown with YAML frontmatter. No SDK required to read or author a document.
- **Governed multi-agent writes.** The single-writer MCP pipeline (advisory locks, per-session worktrees, durable push queue) prevents concurrent write races without requiring distributed locking infrastructure.
- **Queryable by status, tier, and type.** Filter by status: accepted, tier: T1, or type: decision without post-processing. The supersedes chain makes it possible to trace decision history across the graph.
- **Tested with official OKF tooling.** CI pins an exact Google OKF revision and proves both consumption directions over committed fixtures. The pin, fixture checksum, and Apache 2.0 license provenance live in tests/okf/reference.json.
来源
awesome · https://github.com/knaisoma/data-olympus
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