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abhigyan-shekhar-waggle-mcp

Persistent graph memory for AI agents. Drop a conversation turn in via `observe_conversation()` and facts are auto-extracted, stored as typed graph nodes with local semantic embeddings (no API key). Supports temporal queries ("what did we decide last week?"), conflict detection, and context priming. One-command setup with `waggle-mcp init`. SQLite locally, Neo4j in production.

Score
94.6302 signals
Evidence
39 stars · 138 forks
Last commit
as last read from GitHub; most reads are from 2 Sep 2026 or later
Listed

Install

No one-command install. Set it up from its source.

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What it is

Persistent graph memory for AI agents. Drop a conversation turn in via observe_conversation() and facts are auto-extracted, stored as typed graph nodes with local semantic embeddings (no API key). Supports temporal queries ("what did we decide last week?"), conflict detection, and context priming. One-command setup with waggle-mcp init. SQLite locally, Neo4j in production.

When to use it

When an agent needs the "Knowledge & Memory" capability this MCP server exposes.

Source

Migrated from the awesome-mcp-servers navigation directory (category: Knowledge & Memory). See https://github.com/Abhigyan-Shekhar/Waggle-mcp.