Data Olympus

io.github.knaisomav0.11.0更新於 Oct 5, 2026

Governance-grade knowledge-base format (OKF-compatible) plus CLI and single-writer MCP server

概覽

AI 產生的概覽

提供以 git 為基礎的 Markdown 知識庫,讓助理檢索約束編碼決策的工程規範與決策紀錄。

功能
Data Olympus 是一套治理級知識庫格式,附帶單一寫入者的 MCP 伺服器與命令列工具。它會索引由帶 YAML frontmatter 的 Markdown 文件組成的 git 知識包,讓助理依 status、tier 或 type 篩選來搜尋與檢索概念,並沿 supersedes 鏈追蹤文件圖中的決策歷史。它鎖定「編碼意圖到治理規則」的檢索,指出應該約束某項選擇的既有標準或決策,並明確不是程式碼搜尋或引用查找工具。寫入會先進入待處理佇列,搭配諮詢鎖與各工作階段的 worktree,之後才提交。
適用情境
當團隊把工程標準、架構決策與專案知識保存在 git,並希望助理在撰寫程式時參考這些規則時使用。它適合更重視模型與既有模式保持一致、而非定位程式碼的情境。它不用於程式碼搜尋、符號查找或尋找某處的使用方式。
執行需求
需要 Python 3.13 或更新版本以及 uv。套件以 data-olympus 名稱從 PyPI 安裝,包含命令列工具與獨立的 MCP 伺服器指令。設定使用 KB_MAIN_PATH 指向 git 知識包,KB_INDEX_PATH 指向產生的 SQLite 索引,KB_HTTP_PORT 指定 streamable HTTP 伺服器連接埠,預設為 8080。另需一個存放知識包的 git 儲存庫。
安裝前請注意
此伺服器會寫入知識包:擬議的修改先進入待處理佇列再提交,索引會原子重建並替換。它處於 1.0 之前的 beta 階段,行為與格式可能變動。它採用單一寫入者服務模型,不支援並行寫入。在把知識包提供給助理前先檢查內容,因為檢索到的文件會傳送給模型。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Data Olympus,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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, 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.

Quickstart

Requires Python 3.13+ and uv. Run the stable CLI directly from PyPI:

bash
uvx --from data-olympus data-olympus --help

Install it persistently when you are ready to create a bundle and run the server:

bash
uv tool install data-olympusdata-olympus init my-kbdata-olympus-mcp --help

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:

bash
uvx --from 'data-olympus==X.Y.ZrcN' data-olympus --help

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, what server.json declares, 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 in docs/comparison.md.
  • SECURITY.md: supported versions and how to report a vulnerability.

License

Apache 2.0. See LICENSE and NOTICE.

來源:README.md,提交 28a6454

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版本歷史

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  1. v0.11.0最新Oct 5, 2026