Documentation
Build the memory layer from laptop to cloud.
Quickstarts, agent integrations, cloud deployment guides, and the reference material needed to operate Meivo with confidence.
Local quickstart
Install gm-server, start the core engine, and store and recall your first memory locally.
Read guide →Getting startedServer quickstart
Auth, CORS, SQLite vs Postgres, and Docker Compose for a server other machines can reach.
Read guide →Getting startedIngest, use, and remove data
Public examples for adding text and files, using memory in prompts, and deleting imported data by id.
Read guide →CapabilitiesFeature guide
Every capability explained for both decision-makers and engineers - what it does, how to enable it, an example, the benefits, and the trade-offs.
Read guide →AgentsMCP server
Both transports, thirteen memory tools, parameters, examples, and namespace/security boundaries.
Read guide →AgentsClaude Code
Persistent memory for Claude Code with one command.
Read guide →AgentsCodex CLI
Register gm-server mcp in ~/.codex/config.toml.
Read guide →AgentsHermes
stdio MCP configuration for Hermes.
Read guide →AgentsOpenClaw
stdio MCP configuration for OpenClaw.
Read guide →AgentsCustom agents (REST)
curl, Python, and TypeScript clients for the memory loop, plus OpenAPI client generation.
Read guide →IntegrationsGoogle Vertex AI
Use Vertex AI as Meivo's LLM and embedder via the OpenAI-compatible endpoint - models, OAuth token auth, and embedding dimensions.
Read guide →IntegrationsAmazon Bedrock
Use Amazon Bedrock for fact extraction and reflection via the OpenAI-compatible Chat Completions endpoint and a Bedrock API key.
Read guide →IntegrationsAzure OpenAI
Use Azure OpenAI (Azure AI Foundry) as Meivo's LLM and embedder via the OpenAI-compatible v1 API and deployment names.
Read guide →IntegrationsCloud ETL & data management
Managed ETL patterns for Dataflow, Azure Data Factory, and AWS Glue: ingest, use, update, and delete Meivo data.
Read guide →DeploymentAWS
EC2 + Docker Compose, or ECS Fargate with RDS Postgres + pgvector.
Read guide →DeploymentAzure
Container Apps with Azure Files or PostgreSQL Flexible Server; Container Instances as the simple path.
Read guide →DeploymentGoogle Cloud
Cloud Run with Cloud SQL + pgvector, or a GCE VM with a stateful disk.
Read guide →DeploymentEnterprise database (pgvector)
Run Meivo against managed/enterprise Postgres where a DBA provisions pgvector and the app role can't CREATE EXTENSION.
Read guide →DeploymentUpgrades & migrations
Zero-downtime version upgrades: automatic migrations, the readiness probe, rolling deploys, and safe rollback.
Read guide →ReferenceServer command reference
The actual gm-server operational commands, plus pointers to REST/OpenAPI and MCP for memory operations.
Read guide →ReferenceConfiguration reference
Core-engine environment variables, greatmemory.toml keys, operational flags, and feature toggles.
Read guide →ReferenceArchitecture & integration
The enterprise memory framework, supporting gateway/UI, trust boundaries, deployment modes, and integration surfaces.
Read guide →ReferenceCore API keys & offline use
Direct core-engine API keys, offline operation, and the controls required for a sealed deployment.
Read guide →ResearchResearch & roadmap
The memory-systems research that informs Meivo - temporal knowledge graphs, agentic memory, reflection - and how each idea maps onto the engine.
Read guide →