Quipu

Quipu Governed knowledge your agents can read, reuse and share

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.

Install

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:

printf '@prefix : <urn:demo:> .\n:Ada :studies :Engine .\n' > ada.ttl

quipu knot ada.ttl --db demo.db quipu read 'SELECT ?who ?what WHERE { ?who ?what }' --db demo.db

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

printf '@prefix : <urn:demo:> .\n:Babbage :designed :Engine .\n' > babbage.ttl

quipu knot babbage.ttl --db demo.db quipu read 'SELECT ?s ?p ?o WHERE { ?s ?p ?o }' --db demo.db quipu read 'SELECT ?s ?p ?o WHERE { ?s ?p ?o }' --tx 1 --db demo.db

After the first fact After the second fact

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.

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:

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 Quipu book: tutorials, concepts and references.
• Quick Start: governed local examples.
• Domain shapes: producer-owned vocabulary.
• Stack README format and shared hero theme.

🧺 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.

Contributing

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

just check

just docs check

📜 License

Apache-2.0.