Package Exports
- @props-labs/mesh-os
- @props-labs/mesh-os/dist/index.js
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Readme
[!WARNING] This is the experimental TypeScript version of MeshOS. For the stable Python implementation, please visit Props-Labs/mesh-os.
The TypeScript version is under active development and APIs may change frequently. For production use, we recommend using the Python version.
MeshOS
The Memory & Knowledge Engine for Multi-Agent Systems
MeshOS is a developer-first framework for building multi-agent AI-driven operations with structured memory, knowledge retrieval, and real-time collaboration. Unlike generic memory stores, MeshOS is purpose-built for:
- Autonomous Agents & Teams – Agents and humans evolve a shared memory over time.
- Graph-Based Memory – Track relationships, dependencies, and evolving knowledge.
- Fast Semantic Search – Vector-based retrieval with pgvector.
- Event-Driven Execution – Automate workflows based on evolving context.
- Versioned Knowledge – Track updates, past decisions, and historical context.
- Open & Portable – Runs on PostgreSQL + Hasura with no vendor lock-in.
Why MeshOS?
Most frameworks give you a blob of memories—MeshOS gives you structured, evolving intelligence with deep relationships and versioning.
Feature | MeshOS | Mem0 / Letta / Zep |
---|---|---|
Multi-Agent Memory | ✅ Yes | ❌ No |
Structured Taxonomy | ✅ Yes | ❌ No |
Versioned Knowledge | ✅ Yes | ❌ No |
Graph-Based Relationships | ✅ Yes | ❌ No |
Semantic & Vector Search | ✅ Yes | ✅ Partial |
Event-Driven Execution | ✅ Yes | ❌ No |
Open-Source & Portable | ✅ Yes | ✅ Partial |
Who is MeshOS for?
✅ Builders of AI-powered operations – Structured memory and decision-making for AI-driven systems.
✅ Multi-agent system developers – AI agents that need to store, process, and evolve shared knowledge.
✅ Developers & engineers – Wanting an open-source, PostgreSQL-powered framework with no lock-in.
flowchart LR
%% Main System
subgraph MeshOS[MeshOS System]
direction LR
%% Taxonomy Details
subgraph Taxonomy[Memory Classification]
direction TB
subgraph DataTypes[Data Types]
direction LR
knowledge[Knowledge Type]
activity[Activity Type]
decision[Decision Type]
media[Media Type]
end
subgraph Subtypes[Example Subtypes]
direction LR
k_types[Research/Mission/Vision]
a_types[Conversations/Logs/Events]
d_types[Policies/Strategies]
m_types[Documents/Images]
knowledge --> k_types
activity --> a_types
decision --> d_types
media --> m_types
end
subgraph Relations[Edge Types]
direction LR
basic[related_to/version_of]
semantic[influences/depends_on]
temporal[follows_up/precedes]
end
end
%% Memory Operations
subgraph MemoryEngine[Memory Operations]
direction LR
rememberAction[Store/Remember]
recallAction[Search/Recall]
linkAction[Link Memories]
versioning[Version Control]
rememberAction --> recallAction
recallAction --> linkAction
linkAction --> versioning
end
end
%% Organization & Agents
subgraph Organization[Organization & Agents]
direction TB
%% Company Memory
subgraph CompanyMemory[Company-Wide Memory]
direction LR
corpVision[Company Vision]
corpMission[Company Mission]
corpData[Knowledge Base]
end
%% Agents
subgraph Agent1[Research Agent]
a1Mem[Research Memories]
end
subgraph Agent2[Service Agent]
a2Mem[Service Memories]
end
end
%% System Connections
Taxonomy --> MemoryEngine
MemoryEngine --> Organization
%% Memory Connections
corpVision -.->|influences| a1Mem
corpMission -.->|guides| a2Mem
a1Mem -.->|shares| a2Mem
a2Mem -.->|feedback| corpData
a1Mem -.->|versions| corpData
%% Styling
classDef system fill:#dfeff9,stroke:#333,stroke-width:1.5px
classDef engine fill:#fcf8e3,stroke:#333
classDef taxonomy fill:#e7f5e9,stroke:#333
classDef types fill:#f8f4ff,stroke:#333
classDef org fill:#f4f4f4,stroke:#333
class MeshOS system
class MemoryEngine engine
class Taxonomy,DataTypes,Subtypes,Relations taxonomy
class Organization org
Getting Started
Important Note: The JavaScript client can only connect to an existing MeshOS instance. To launch a new MeshOS system, please use the Python version which includes deployment capabilities.
Usage
import { MeshOS } from '@props-labs/mesh-os';
import dotenv from 'dotenv';
// Load environment variables
dotenv.config();
// Connect To MeshOS
const client = new MeshOS({
url: process.env.HASURA_URL || 'http://localhost:8080',
apiKey: process.env.HASURA_ADMIN_SECRET || 'meshos',
openaiApiKey: process.env.OPENAI_API_KEY
});
// Register an agent with a slug
const agent = await client.registerAgent(
'AI_Explorer',
'An agent for exploring data',
{ role: 'explorer' },
'ai-explorer'
);
// Store structured knowledge
const memory = await client.remember(
'The Moon has water ice.',
agent.id,
{
type: 'knowledge',
subtype: 'fact',
tags: ['astronomy', 'moon'],
version: 1
}
);
// Retrieve similar knowledge
const results = await client.recall('Tell me about the Moon.', {
agentId: agent.id,
limit: 5,
threshold: 0.7
});
🏗️ Core Features
✅ Memory for Multi-Agent Systems – Let agents store, retrieve, and link structured knowledge.
✅ Fast Semantic Search – pgvector-powered similarity matching across all memories.
✅ Graph-Based Knowledge – Build evolving relationships between facts, ideas, and actions.
✅ Versioning Built-In – Track updates, past decisions, and context shifts.
✅ Event-Driven Execution – Automate workflows based on new knowledge.
✅ Open & Portable – Runs anywhere PostgreSQL does. No black-box infrastructure.
🔗 Structured Taxonomy & Memory Graph
MeshOS enforces structured knowledge with memory classification and versioning:
Memory Type | Examples |
---|---|
Knowledge | Research reports, datasets, concepts |
Activity | Agent workflows, logs, system events |
Decision | Policy updates, business strategy |
Media | Documents, images, AI-generated content |
Memories evolve over time, with full versioning and relationship tracking.
🛠️ Development & Configuration
Configuration
# Required
OPENAI_API_KEY=your_api_key_here
# Optional (defaults shown)
POSTGRES_PASSWORD=mysecretpassword
HASURA_ADMIN_SECRET=meshos
POSTGRES_PORT=5432
HASURA_PORT=8080
HASURA_ENABLE_CONSOLE=true
Development
git clone https://github.com/props-labs/mesh-os.git
cd mesh-os
pnpm install
pnpm build
pnpm test
Contributing
Contributions are welcome! Please submit a Pull Request.
⚖️ License
This project is licensed under the MIT License – see LICENSE for details.