Quipu

io.github.scbrown由 GitHub 账号 scbrown 发布v0.15.0更新于 Oct 24, 2026

Local knowledge graph memory for agents. SHACL rules refuse bad facts; SPARQL and time travel.

概览

AI 生成的概览

Quipu 是面向 AI 代理的本地受治理知识图谱记忆,让助手保存带来源的事实,并查询当前或历史状态。

可以做什么
  • 把以 Turtle 编写的事实写入本地图数据库,写入时按你的词汇表与形状进行校验
  • 用 SPARQL 查询图谱,并可查询早期版本的数据以回答时间回溯问题
  • 对已存知识做关键词检索,配置嵌入模型后可做语义检索
  • 导入经过校验的知识包,先暂存新事实而不改动现有根数据
  • 在多个代理与工具之间共享项目事实、决策与关系,无需重复粘贴上下文
适用场景
适合希望助手把持久、可审计的项目知识(事实、决策及其历史)集中保存在一个本地存储中,供多个代理和工具读取复用的场景,而不是每次会话都重复粘贴同样的上下文。
运行要求
以 stdio 本地进程方式运行,启动时指定数据库路径,可通过 Docker 镜像或命令行工具启动。命令行工具面向 Linux 和 macOS 的 x86_64 与 arm64,安装需要 Python 3.9+ 和 curl。未声明任何环境变量、请求头或身份验证。语义检索需安装嵌入模型;全新存储可直接使用关键词检索。
安装前请注意
服务器会读写本地数据库文件,请指向预期的存储并做好备份。导入和写入会改变已存知识,尽管导入被描述为先暂存而不改动现有根数据。语义检索需要下载模型。README 的安装步骤把远程脚本直接交给 shell 执行,运行前应先审查。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Quipu,将其添加到工作区。
  2. 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

[Quipu logo: knotted strings forming a knowledge graph]

Quipu

Governed knowledge your agents can read, reuse and share

[License: Apache-2.0] [CI] [crates.io: quipu-ai] [Docs: the Quipu book] [DOI: 10.5281/zenodo.21878428] [arXiv: 2608.16813] [Part of the Tambo stack]

Read the book →

Quipu is a governed, bitemporal knowledge store for AI agents and the people who run them. Use it from the command line, REST, MCP or a Rust application.

Why you would want it

  • Governed: check incoming knowledge against your vocabulary and shapes.
  • Bitemporal: keep a queryable history of facts and decisions.
  • Reusable agent knowledge: store memory agents can read, reuse and share across tools.
  • Time-aware entities: attach event-triggering time attributes for Chaski to react to.

Use Quipu as the central graph and base for many tools: see the stack. The full case is in Why Quipu.

[Animated: one Quipu store connects the CLI, MCP clients, HTTP server, Rust library, offline use and WebAssembly]

Install

sh
curl -fsSL https://raw.githubusercontent.com/intigraph/quipu/main/install.sh | sh

Linux and macOS, x86_64 and arm64; requires Python 3.9+ and curl. The installer verifies the published archive checksum and executable version. Then run quipu --version. Install, upgrade or remove Quipu. For the whole stack, use Tambo's guided onboarding.

First success: insert a fact, watch the graph change

Write one fact in plain Turtle, knot it into a local store, and ask for it back:

sh
printf '@prefix : <urn:demo:> .\n:Ada :studies :Engine .\n' > ada.ttlquipu knot ada.ttl --db demo.dbquipu read 'SELECT ?who ?what WHERE { ?who <urn:demo:studies> ?what }' --db demo.db

Add a second fact and the graph grows. The first version is still there to query:

sh
printf '@prefix : <urn:demo:> .\n:Babbage :designed :Engine .\n' > babbage.ttlquipu knot babbage.ttl --db demo.dbquipu read 'SELECT ?s ?p ?o WHERE { ?s ?p ?o }' --db demo.dbquipu read 'SELECT ?s ?p ?o WHERE { ?s ?p ?o }' --tx 1 --db demo.db

[Animated terminal: two plain facts are inserted and queried, then the earlier version is read back]

Transcript, tool version and reproducible capture.

On your own code

Keep project facts, decisions and relationships together instead of pasting the same context into each agent.

You want toStart here
Load facts and apply your vocabularyQuick Start
Ask about current or historical knowledgeSPARQL and time
Share a governed knowledge bundleVerified sharing
Prepare domain knowledge and shapesCamayoc

[Animated: export a share, verify it in quarantine, then explicitly promote admitted knowledge; conflicts are not silently merged]

The latest release includes a repository pendant, checksum and provenance. Verify them together, then use quipu import SHARE_DIR --db repository.db; import stages knowledge and leaves ROOT unchanged. Follow the verified import workflow.

Wire it into your agent

For Claude Code, connect the local MCP server to your database:

sh
claude mcp add quipu -- quipu mcp --db /path/to/knowledge.db

The MCP Registry identifier is mcp-name: io.github.intigraph/quipu. Other clients, HTTP MCP and credential configuration: Agent Setup. Use Tambo to configure and verify the tools together.

Before you start

  • The CLI runs locally; quipu-server supplies the network API and explorer.
  • Fresh stores support keyword search without downloading a model. quipu search "your terms" uses keyword search until an embedding provider is configured; explicit --mode semantic still requires a model and vectors. Install the pinned default model with quipu model install in a full build. Check readiness with quipu doctor search.
  • Configuration covers storage and server settings.

What's next

🧺 The stack

Tambo installs these together and proves each one works; every tool also stands alone. Use each tool's README for its own installation and first success.

The Quipu stack is built around a governed, bitemporal knowledge store: shared facts, decisions and work history your agents can query. Quipu can check writes against your rules, records where each fact came from, and answers what was true when.

toolwhat it gives your agents
tambo🧰 Agent Platform Toolkit - installs and configures the quipu stack
quipustores shared facts with provenance and history; can check writes against your rules
camayocprepares knowledge and vocabulary for Quipu, with checks before it is admitted
quechuashared vocabulary and shapes for interoperable knowledge
chaskireacts to graph changes and delivers governed notifications
bobbinindexes your codebase and injects context from that index and Quipu knowledge
yupanashows code impact and can read policies from Quipu to govern agent actions
desire-pathturns agent mistakes into feature requests; works on its own without Quipu
seedsa work item tracker backed by the Quipu knowledge base
shantytownruns crews of AI agents on work items, triggered by hand, on a schedule or by events; can share work and memory through Quipu
rikuylive brief: status, graphs, watches and signed decisions over Quipu
shuttleruns signed agent workflows and keeps their records in Quipu

Contributing

See CONTRIBUTING.md. The repository's checks are:

sh
just checkjust docs check

📜 License

Apache-2.0.

来源:README.md,提交 2289024

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

10
  1. v0.15.0最新Oct 20, 2026
  2. v0.14.1Oct 15, 2026
  3. v0.14.0Oct 15, 2026
  4. v0.13.0Oct 14, 2026
  5. v0.12.0Oct 10, 2026
  6. v0.11.1Oct 8, 2026
  7. v0.11.0Oct 3, 2026
  8. v0.10.0Oct 2, 2026
  9. v0.9.1Sep 30, 2026
  10. v0.9.0Sep 26, 2026

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