mesh-memory
Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.
Mesh Memory
Mesh Memory is a self-hosted semantic memory service with a built-in MCP server. It stores documents (worklogs, decisions, notes, research) in PostgreSQL with pgvector and retrieves them by meaning, so a query like "what database did we pick?" surfaces a saved note that says "chose Redis for caching" even with zero keyword overlap. Embeddings are generated locally with multilingual-e5-base (768 dimensions); the core flow requires no external API keys.
Use this skill when an agent needs persistent memory across sessions: saving its own work, recalling prior decisions, or building a project knowledge base shared between multiple agents.
When to Use This Skill
- Saving a session worklog, decision, or research note so a later session can find it.
- Recalling past work by topic when you do not remember the exact words you used.
- Sharing a long-lived knowledge base across multiple agents, terminals, or teammates.
- Organizing context by role or project through workspaces (one workspace per role/project).
- Looking up structured tags (e.g. all
type:decisionentries from one project).
Prerequisites
- A running Mesh Memory instance reachable from the MCP server. Local Docker is the common path --
docker compose up -din the upstream repo brings it up; see https://github.com/dklymentiev/mesh-memory for the full Quick Start. - The MCP server (`mcp_server.
Subscribers only
The full skill, its 1 bundled files and every download is included with every paid Complete AI plan.
Details
| Source | dklymentiev/mesh-memory (MIT) |
|---|---|
| License | — |
| Risk label | safe ("critical" means the skill may run commands or touch files — read before use) |
| Files | SKILL.md |
| Added | 2026-05-23 |
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