
Data Olympus
io.github.knaisomav0.11.0更新于 Oct 5, 2026
Governance-grade knowledge-base format (OKF-compatible) plus CLI and single-writer MCP server
概览
提供基于 git 的 Markdown 知识库,让助手检索约束编码决策的工程规范与决策记录。
- 功能
- Data Olympus 是一套治理级知识库格式,附带单写入者的 MCP 服务器和命令行工具。它索引一个由带 YAML frontmatter 的 Markdown 文档组成的 git 知识包,让助手按 status、tier 或 type 过滤来搜索和检索概念,并沿 supersedes 链追踪文档图中的决策历史。它面向“编码意图到治理规则”的检索,给出应当约束某项选择的既有标准或决策,并明确不是代码搜索或引用查找工具。写入先进入待处理队列,配合咨询锁和按会话的工作树,然后才提交。
- 适用场景
- 当团队把工程标准、架构决策和项目知识保存在 git 中,并希望助手在编码时参考这些规则时使用。它适合更看重模型与既有模式保持一致、而非定位代码的场景。它不用于代码搜索、符号查找或查找某处用法。
- 运行要求
- 需要 Python 3.13 或更高版本以及 uv。软件包以 data-olympus 名称从 PyPI 安装,包含命令行工具和单独的 MCP 服务器命令。配置使用 KB_MAIN_PATH 指向 git 知识包,KB_INDEX_PATH 指向生成的 SQLite 索引,KB_HTTP_PORT 指定 streamable HTTP 服务器端口,默认 8080。还需要一个存放知识包的 git 仓库。
安装
在 SourceWeft 中
- 打开 控制台中的 Data Olympus,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
data-olympus
[knaisoma/data-olympus MCP server] [MCP Marketplace]
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, ortype: decisionwithout post-processing. Thesupersedeschain 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.
Quickstart
Requires Python 3.13+ and uv. Run the stable CLI
directly from PyPI:
Install it persistently when you are ready to create a bundle and run the server:
An announced candidate remains opt in through its exact PyPI version. Replace
X.Y.ZrcN with the candidate named on the
releases page, if any:
See release channels for what each channel means, how to verify a candidate before adopting it, and how to roll back.
See docs/quickstart.md for bundle initialization, server startup, readiness,
agent registration, and the contributor source installation.
See docs/adoption.md for the full bundle authoring guide.
Documentation
SPEC.md: format specification (bundle layout, frontmatter schema, serving contracts).docs/quickstart.md: verified local-run procedure.docs/adoption.md: bring-your-own-KB guide (author, lint, index, serve, wire an agent).docs/serving.md: single-replica serving model, read-only replicas, git pull loop, health/readiness/liveness split, proxy headers, audit-log rotation.docs/operations.md: production runbook: backup, upgrade, recovery playbooks (degraded/fetch-failed, history rewrite, frozen/demoted push entries, orphaned locks), the health/alerting model, and release channels (stable and candidate, verification, rollback).docs/comparison.md: how data-olympus relates to OKF, enterprise catalogs, markdown KB tools, agent-context conventions, RAG, and ADR tooling.docs/okf-profile.md: field-by-field OKF profile: which governance extensions are stable, which are runtime-only serving fields, and which are experimental candidates.docs/glama.md: Glama registry claim, release, and score-maintenance notes.docs/mcp-registry.md: official MCP Registry notes, whatserver.jsondeclares, and the checklist for publishing.docs/enforcement.md: turning the KB into a mandatory consultation gate (hooks,kb enforce).benchmarks/README.md: retrieval benchmark methodology and how to reproduce the numbers indocs/comparison.md.SECURITY.md: supported versions and how to report a vulnerability.
License
来源:README.md,提交 28a6454
工具
0版本历史
1- v0.11.0最新Oct 5, 2026

