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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.

AI & Automation

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:decision entries from one project).

Prerequisites

  • A running Mesh Memory instance reachable from the MCP server. Local Docker is the common path -- docker compose up -d in 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

Sourcedklymentiev/mesh-memory (MIT)
License
Risk labelsafe ("critical" means the skill may run commands or touch files — read before use)
FilesSKILL.md
Added2026-05-23

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