Lakehouse graph database for context assembly & multi-agent coordination
Multimodal retrieval · Git-style branching · object-storage native
Quickstart · Docs · Cookbooks · CLI
Omnigraph is the operational state and coordination layer for fleets of agents.
Run it as a server, declared as code; hundreds of agents operate and enrich the graph on parallel isolated branches, and every change is reviewed and merged safely.
| Capability | What it gives you |
|---|---|
| Declared as code | |
A cluster.yaml declares graphs, schemas, stored queries, embedding providers, and policies; cluster apply converges it and omnigraph-server brings every graph online at /graphs/{id}/… . |
|
| Built for fleets of agents | |
| Hundreds of agents enrich the graph on parallel isolated branches; changes are reviewed and merged safely, Git-style, across the whole graph. | |
| Multimodal retrieval | |
| Graph traversal + vector ANN + full-text + Reciprocal Rank Fusion in one query runtime, for context assembly. | |
| Security as code | |
| Cedar policy enforced server-side on every mutation, per-graph and server-wide; bearer auth; actor/audit tracking. | |
| Runs on your infrastructure | |
| Any S3-compatible object store: on-prem via RustFS / MinIO, or AWS S3 / R2 / GCS. VPC, on-prem, hybrid; your data never leaves your store. | |
| Open, versioned storage | |
Lance |
| Use case | What it's for |
|---|---|
| Company brain | |
| Org knowledge unified into one graph every agent can query | |
| Agentic memory | |
| Durable, versioned memory: a branch per agent or per task, merged on review | |
| Context graph | |
| Decision traces and codified tribal knowledge for retrieval | |
| Dev graph | |
| Issues & dependency model that coding agents read and write | |
| R&D / ML data layer | |
| Experiments and trials written into branches, versioned for training & eval |
curl -fsSL https://raw.githubusercontent.com/ModernRelay/omnigraph/main/scripts/install.sh | bash
This installs omnigraph
(CLI) and omnigraph-server
into ~/.local/bin
from published release binaries. Or with Homebrew:
brew tap ModernRelay/tap
brew install ModernRelay/tap/omnigraph
Omnigraph is built to be run by coding agents. Two ways in:
Teach your agent the playbook. This repo ships the : the operational playbook covering cluster mode, the two config surfaces, schema evolution, query linting, data writes, branches, Cedar policy, and the common gotchas.
omnigraph
agent skill
npx skills add ModernRelay/omnigraph@omnigraph
Or have an agent set it up from scratch. Paste this into Claude Code, Codex, or any agent that can read a URL and run a shell command:
Help me set up Omnigraph
1. Read the docs at https://github.com/ModernRelay/omnigraph, starting with
docs/user/clusters/index.md, then docs/user/deployment.md.
2. Skim the starter graphs and seed data in the cookbooks:
https://github.com/ModernRelay/omnigraph-cookbooks
3. Ask me what I want to build (company brain, agent memory, dev graph,
research / R&D layer, …). Then stand up a cluster for it, load a little
data, and run a query so I can see it working.
For ready-to-run graphs with real seed data (company brain, VC operating system, pharma & industry intel), ModernRelay/omnigraph-cookbooks is the fastest way to see Omnigraph shaped to a real domain.
A deployment is a cluster: a multigraph config directory that declares
its graphs, schemas, stored queries, and policies as code. You manage it
Terraform-style: cluster plan
previews the diff, cluster apply
converges
it. omnigraph-server
then boots from the cluster and brings every graph online
at /graphs/{id}/…
, each behind its own policy.
1. Declare the cluster.
company-brain/
├── cluster.yaml
├── people.pg # schema for the "knowledge" graph
├── queries/ # stored queries: the .gq files ARE the declaration
│ └── people.gq
└── base.policy.yaml # a Cedar policy bundle
version: 1
metadata:
name: company-brain
storage: s3://company/clusters/company-brain # ledger, catalog, and graph data live here
graphs:
knowledge:
schema: people.pg
queries: queries/ # every `query <name>` in queries/*.gq registers
policies:
base:
file: base.policy.yaml
applies_to: [knowledge] # graph-bound; use [cluster] for server-level
2. Stand up your object store. On-prem, run RustFS (or MinIO); Omnigraph
writes Lance to it over the standard S3
API. In the cloud, point the same AWS_*
env at S3 / R2 / GCS instead.
3. Converge and run. apply
creates each graph, applies its schema, and publishes queries and policies into the content-addressed catalog. It is idempotent; re-running is always safe.
omnigraph cluster validate # parse + typecheck everything
omnigraph cluster plan # preview what apply would do
omnigraph cluster apply # converge
omnigraph-server --cluster company-brain --bind 0.0.0.0:8080
See the cluster guide for the day-2 loop
(edit → plan → apply → restart), approval gates for destructive changes, drift
inspection, and recovery; the deployment guide for
containers, AWS/Railway, auth, and the full AWS_*
contract.
Set a default server and graph once in ~/.omnigraph/config.yaml
, and the everyday commands stay short. Stored queries and mutations run by name:
omnigraph query search_docs --params '{"q":"AI safety"}'
omnigraph mutate add_person --params '{"name":"Mina"}'
omnigraph branch create --from main agent/ingest-42
omnigraph branch merge agent/ingest-42 --into main
An alias is shorter still: bind a server, graph, and stored query to one
name, then omnigraph alias triage
runs it. For an ad-hoc target, any command
still takes --server <name|url> --graph <id>
(or --store <uri>
for a local graph). See the CLI reference.
Engine-wide enforcement: every write path goes through the same Cedar gate, so the HTTP server, the CLI, and the embedded SDK obey identical rules.Declared in the cluster: a policy bundle is bound to graphs (or the whole server) viapolicies:
→applies_to
.Scoped: rules apply per graph, per branch, or server-wide.No plaintext tokens: bearer tokens are hashed at startup and compared in constant time.Forge-proof identity: the actor is resolved server-side from the token; clients can't set it.
See the policy guide.
| Client | Use it for | Where |
|---|---|---|
| TypeScript SDK | ||
| typed access from Node / TS | ||
@modernrelay/omnigraph |
MCP server@modernrelay/omnigraph-mcp
**HTTP / OpenAPIPython SDK coming soonBoth npm packages are versioned in lockstep with omnigraph-server
.
1-min setup to try it: an embedded, local file-backed graph (no server, no object store). For dev and experiments; production is the deployed cluster above.
cat > schema.pg <<'PG'
node Signal { slug: String @key, title: String }
node Pattern { slug: String @key, name: String }
edge Indicates: Signal -> Pattern
PG
printf '%s\n' \
'{"type":"Signal","data":{"slug":"s1","title":"OSS model adoption surging"}}' \
'{"type":"Pattern","data":{"slug":"p1","name":"adoption"}}' \
'{"edge":"Indicates","from":"s1","to":"p1"}' > data.jsonl
omnigraph init --schema schema.pg ./graph.omni
omnigraph load --data data.jsonl --mode overwrite --store ./graph.omni
omnigraph query --store ./graph.omni \
-e 'query indicates() { match { $s: Signal { slug: "s1" } $s indicates $p } return { $p.name } }'
cargo build --workspace
cargo test --workspace
Notes:
-
Rust stable toolchain, edition 2024
-
CI runs
cargo test --workspace --locked -
Full CI and some local test flows require
protobuf-compiler -
S3 integration tests expect an S3-compatible endpoint such as RustFS
crates/omnigraph-compiler
: shared schema/query parser, typechecker, catalog, and IR lowering (zero Lance dependency)crates/omnigraph
(packageomnigraph-engine
): storage/runtime, branching, merge, change detection, query execution, and embeddingscrates/omnigraph-policy
: Cedar policy compilation and enforcementcrates/omnigraph-api-types
: shared HTTP wire DTOs used by both the server and the CLIcrates/omnigraph-cluster
: cluster config validation, planning, and apply (the control plane)crates/omnigraph-server
: Axum HTTP server, cluster-first, runs N graphs under/graphs/{id}/…
crates/omnigraph-cli
: CLI for graph lifecycle, query/mutate, branch/commit/merge, schema/lint, snapshot/export, cluster control, policy/queries, profiles, and maintenance
Please open an issue, spec, or design discussion before sending large code changes. Design feedback and concrete problem statements are the fastest way to collaborate on the roadmap.
Join the Omnigraph Slack community to ask questions, share feedback, and follow development.