Waggle Mcp vs Agent Memory

In-depth architectural comparison of the Waggle Mcp and Agent Memory MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.

Which MCP Server Should You Choose?

Choose Waggle Mcp when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• You have access to required keys: WAGGLE_MODEL, PYTHONUTF8.
• Primary tools included: Typed graph nodes with local semantic embeddings, Temporal querying of stored facts and decisions, Conflict detection in memory graph.

Explore Waggle Mcp Details

Choose Agent Memory when:

• You need dedicated capabilities in the Knowledge & Memory domain.
• You prefer local stdio subprocess transport architecture.
• Your security boundary fits: No auth required (Free / Open Source).
• Primary tools included: Three-layer memory: identity, active context, and archive, Semantic recall by meaning rather than keywords, Graph memory tracking updates, extensions, derivations, and expirations.

Feature & Specification Comparison

Specification	Waggle Mcp Abhigyan-Shekhar Knowledge & Memory	Agent Memory g1itchbot8888-del Knowledge & Memory
Summary	Persistent graph memory for AI agents. Drop a conversation turn in via observeconversation() 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.	Three-layer memory system for agents (identity/active/archive) with semantic search, graph relationships, conflict detection, and LearningMachine. Built by an agent, for agents. No API keys required.
Category & Scope

Tools & Capabilities Breakdown

Ready-to-Paste Client Configurations

Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).

{
  "mcpServers": {
    "abhigyan-shekhar-waggle-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "abhigyan-shekhar-waggle-mcp"
      ],
      "env": {
        "WAGGLE_MODEL": "YOUR_WAGGLE_MODEL_HERE",
        "PYTHONUTF8": "YOUR_PYTHONUTF8_HERE"
      }
    }
  }
}

{
  "mcpServers": {
    "g1itchbot8888-del-agent-memory": {
      "command": "uvx",
      "args": [
        "openclaw-memory"
      ]
    }
  }
}

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