Understand the project
Practical overview
When it fits
Use Cognio when an assistant workflow needs context to persist beyond an individual conversation and you want project-organized semantic retrieval.
Who it is for
- People building workflows with MCP-compatible AI assistants.
- Users who want a persistent store for research notes, learning records, or multi-project context.
Documented uses
- Save information from conversations for later retrieval.
- Search stored memories by meaning and filter them by project.
- Organize, summarize, and export assistant memory.
Before you choose
Requirements & limits
The repository is public and specifies an MIT license. Its quick start describes running the server locally with Docker Compose.
- Cognio is a memory server that an assistant connects to through MCP, rather than an AI assistant.
- The documented stack includes Python 3.11 or later, SQLite, and a separate MCP server component.
- LEANN vector search is optional; auto-tagging can use an LLM provider and requires provider credentials.
- The repository lists integrations for several assistant clients, but client-specific setup is described separately.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Source-based practical guide
Start Cognio with Docker Compose
Bring up the Cognio server using the repository's quick-start procedure.
Before you start
- Git
- Docker Compose
Steps
Clone the Cognio repository.
Change into the Cognio directory.
Run docker-compose up -d.
Expected outcome
The quick start says the server runs at http://localhost:8080.
Guide limitations
- This procedure starts the server; it does not cover connecting a particular assistant client.
Evidence and transparency
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- 0xReLogic/Cognio · Official homepage title · retained in its source language