AI coding agents are stateless. Every new session starts from zero. The "solutions" either lock you into one model provider or send your codebase
Omega Memory MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. AI coding agents are stateless. Every new session starts from zero. The "solutions" either lock you into one model provider or send your codebase context to their cloud.
Once Omega Memory is connected, these are the calls the assistant has available:
omega_store — Store typed memory (decision, lesson, error, summary)omega_query — Semantic search with tag filters and contextual re-rankingomega_welcome — Session briefing with recent memories and profileomega_profile — Read or update user profileomega_delete_memory — Delete a specific memory by IDomega_edit_memory — Edit the content of a memoryomega_list_preferences — List all stored user preferencesomega_health — Detailed health check with memory usage and recommendationsomega_backup — Export or import memories for backup/restoreomega_lessons — Cross-session lessons ranked by access countomega_feedback — Record feedback on a surfaced memoryomega_clear_session — Clear all memories for a specific sessionomega-memory on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Among the knowledge and memory options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Omega Memory's toolset — omega_store, omega_query, omega_welcome and 11 more — is a fair guide to whether it matches your workflow. It is maintained by omega-memory; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| omega_store | Store typed memory (decision, lesson, error, summary) |
| omega_query | Semantic search with tag filters and contextual re-ranking |
| omega_welcome | Session briefing with recent memories and profile |
| omega_profile | Read or update user profile |
| omega_delete_memory | Delete a specific memory by ID |
| omega_edit_memory | Edit the content of a memory |
| omega_list_preferences | List all stored user preferences |
| omega_health | Detailed health check with memory usage and recommendations |
| omega_backup | Export or import memories for backup/restore |
| omega_lessons | Cross-session lessons ranked by access count |
| omega_feedback | Record feedback on a surfaced memory |
| omega_clear_session | Clear all memories for a specific session |
| omega_similar | Find memories similar to a given one |
| omega_timeline | Memories grouped by day |
{
"mcpServers": {
"omega-memory": {
"command": "uvx",
"args": ["omega-memory"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.