Membrane

Membrane is a selective learning and memory substrate for LLM agents. It gives agents typed, revisable memory instead of an append-only transcript or a flat vector store.

Use it when an agent needs to remember facts, retrieve prior context, revise stale knowledge, preserve task state, and cite the records that informed an answer.

What It Provides

• Five memory layers plus entities: episodic, working, semantic,

competence, plan graph, and canonical entity nodes that connect them.

• Entity-connected retrieval: RetrieveGraph returns ranked records plus

bounded graph neighborhoods, not only top-k chunks.

• Capture-first ingestion: CaptureMemory accepts events, observations,

tool outputs, working state, and facts, then creates linked records and edges.

• Revision operations: supersede, fork, retract, merge, and contest records

with audit trails.

• Decay and reinforcement: salience changes over time and can be reinforced

or penalized by outcomes.

• Trust-aware access: retrieval filters or redacts records using sensitivity,

authentication, and scope checks.

• Multiple runtimes: run membraned over gRPC, use the embedded Go API, or

call it from TypeScript/Python SDKs.

• Self-hosted docs: docs are Docusaurus-based and deployable to Cloudflare

Workers with Wrangler.

Memory Model

The entity layer is not a replacement for the five memory layers. It is the shared graph layer that lets facts, episodes, procedures, plans, and task state retrieve together.

Quick Start

Requirements

• Go 1.22+
• Make
• Node.js 20+ for the TypeScript SDK, docs, and examples
• Python 3.10+ for the Python SDK
• protoc only when regenerating protobuf code

Build And Run

git clone https://github.com/BennettSchwartz/membrane.git
cd membrane

make build
./bin/membraned

By default, membraned uses local SQLite storage. To use Postgres:

./bin/membraned \
  --postgres-dsn "postgres://membrane:membrane@localhost:5432/membrane?sslmode=disable"

Useful commands:

make test                 # Go test suite
make proto                # Regenerate Go protobuf bindings
make ts-build             # Build the TypeScript SDK
make eval-all             # Targeted evaluation suite

TypeScript SDK

npm --prefix clients/typescript install
npm --prefix clients/typescript run build

import {
  MembraneClient,
  MemoryType,
  Sensitivity,
  SourceKind,
} from "@bennettschwartz/membrane";

const client = new MembraneClient("localhost:9090", {
  apiKey: process.env.MEMBRANE_API_KEY,
});

const capture = await client.captureMemory(
  {
    subject: "auth-service",
    predicate: "uses_database",
    object: "PostgreSQL",
  },
  {
    source: "agent",
    sourceKind: SourceKind.OBSERVATION,
    summary: "auth-service uses PostgreSQL",
    tags: ["auth-service", "postgres"],
    scope: "project-orion",
    sensitivity: Sensitivity.LOW,
  },
);

const graph = await client.retrieveGraph("debug auth-service latency", {
  trust: {
    max_sensitivity: Sensitivity.MEDIUM,
    authenticated: true,
    actor_id: "debug-agent",
    scopes: ["project-orion"],
  },
  memoryTypes: [
    MemoryType.ENTITY,
    MemoryType.EPISODIC,
    MemoryType.WORKING,
    MemoryType.SEMANTIC,
    MemoryType.COMPETENCE,
    MemoryType.PLAN_GRAPH,
  ],
  rootLimit: 12,
  nodeLimit: 64,
  edgeLimit: 160,
  maxHops: 2,
});

console.log(capture.primary_record.id, graph.nodes.length);
client.close();

See clients/typescript for the full SDK.

Python SDK

python -m pip install -e "clients/python[dev]"
python -m pytest clients/python/tests

from membrane import MembraneClient, MemoryType, Sensitivity, SourceKind

client = MembraneClient("localhost:9090")

capture = client.capture_memory(
    {
        "thread_id": "incident-42",
        "state": "investigating auth-service latency",
        "next_actions": ["check database wait", "hold canary"],
    },
    source="agent",
    source_kind=SourceKind.WORKING_STATE,
    summary="Incident state updated",
    tags=["auth-service", "incident"],
    sensitivity=Sensitivity.LOW,
)

graph = client.retrieve_graph(
    "auth-service canary incident",
    memory_types=[
        MemoryType.ENTITY,
        MemoryType.WORKING,
        MemoryType.SEMANTIC,
        MemoryType.COMPETENCE,
        MemoryType.PLAN_GRAPH,
    ],
)

print(capture.primary_record.id, len(graph.nodes))
client.close()

See clients/python for package details.

Go Library

Membrane can also run embedded in a Go process:

package main

import (
	"context"
	"log"

	"github.com/BennettSchwartz/membrane/pkg/ingestion"
	"github.com/BennettSchwartz/membrane/pkg/membrane"
	"github.com/BennettSchwartz/membrane/pkg/retrieval"
	"github.com/BennettSchwartz/membrane/pkg/schema"
)

func main() {
	m, err := membrane.New(membrane.DefaultConfig())
	if err != nil {
		log.Fatal(err)
	}
	defer m.Stop()

	ctx := context.Background()
	if err := m.Start(ctx); err != nil {
		log.Fatal(err)
	}

	capture, err := m.CaptureMemory(ctx, ingestion.CaptureMemoryRequest{
		Source:     "agent",
		SourceKind: "observation",
		Content: map[string]any{
			"subject":   "auth-service",
			"predicate": "uses_database",
			"object":    "PostgreSQL",
		},
		Summary: "auth-service uses PostgreSQL",
		Tags:    []string{"auth-service", "postgres"},
	})
	if err != nil {
		log.Fatal(err)
	}

	graph, err := m.RetrieveGraph(ctx, &retrieval.RetrieveGraphRequest{
		TaskDescriptor: "debug auth-service latency",
		Trust: &retrieval.TrustContext{
			MaxSensitivity: schema.SensitivityMedium,
			Authenticated:  true,
		},
		MemoryTypes: []schema.MemoryType{
			schema.MemoryTypeEntity,
			schema.MemoryTypeSemantic,
			schema.MemoryTypeCompetence,
		},
		RootLimit: 10,
		MaxHops:   2,
	})
	if err != nil {
		log.Fatal(err)
	}

	log.Printf("captured=%s graph_nodes=%d", capture.PrimaryRecord.ID, len(graph.Nodes))
}

Documentation

The docs site lives in docs, is built with Docusaurus, and is deployed to Cloudflare Workers at <https://membrane.gustycube.com>.

npm install
npm run docs:dev
npm run docs:build

# Deploy to Cloudflare Workers when Wrangler is configured
npm run docs:deploy

Cloudflare configuration is in wrangler.jsonc. The GitHub Actions deploy workflow runs when docs files change and deploys when CLOUDFLARE_API_TOKEN is present as a repository secret. The membrane.gustycube.com DNS record must be proxied through Cloudflare for the Worker route to receive production traffic. Sidebar and theme configuration live in sidebars.js and docusaurus.config.js.

API Surface

The gRPC API is defined in api/proto/membrane/v1/membrane.proto. Core RPCs include:

• CaptureMemory
• RetrieveGraph
• RetrieveByID
• Supersede
• Fork
• Retract
• Merge
• Contest
• Reinforce
• Penalize
• GetMetrics

Generated Go, TypeScript, and Python bindings are committed so consumers do not need protobuf tooling for normal development.

Storage And Configuration

Membrane supports SQLite for local and embedded use, and Postgres for concurrent deployments. Postgres can optionally use pgvector for embedding-backed ranking.

Common environment variables:

See docs/guides/configuration.mdx for full configuration details.

Project Layout

api/                  Protobuf definitions and generated Go gRPC bindings
clients/typescript/   TypeScript SDK
clients/python/       Python SDK
cmd/membraned/        Daemon entrypoint
docs/                 Docusaurus docs content
examples/             Reference examples and experiments
pkg/                  Core Go packages
tests/                Evaluation and integration tests

Development

Run the checks most often used before committing:

make build
make test
npm --prefix clients/typescript run build
npm run docs:build

Contributing

Issues and PRs are welcome. See CONTRIBUTING.md for local workflow and expectations.

License

MIT. See LICENSE.