Waggle Mcp

Install Waggle Mcp

Install instructions vary — visit the GitHub repository for the latest install command. Most MCP servers follow one of three patterns: npx -y <package> for Node, uvx <package> for Python, or docker run <image> for containerized servers.

Use Waggle Mcp with Claude Code

Once the server is on your machine, register it with Claude Code so the agent can call it like any other tool. The general pattern is:

claude mcp add abhigyan-shekhar-waggle-mcp -- <install-command>

After it's registered, run claude and ask anything that requires Waggle Mcp. Claude Code will negotiate the MCP handshake and surface the server's tools, prompts, and resources to the model automatically. See our Claude Code MCP guide for environment variables, scope flags, and credential handling.

What this server is for

Waggle Mcp sits in the knowledge & memory category. It's community-maintained — check the repo's last-commit date and open issues before depending on it in production. The full description from the source list:

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.

FAQ

Is Waggle Mcp free?

Yes — every MCP server in the ClawHire directory is open-source or freely available. Some servers proxy to paid APIs (you supply your own keys), but the server itself is free.

Does it work with Claude Desktop / Cursor / Windsurf?

If a client speaks the Model Context Protocol, it can use this server. The transport (stdio vs SSE vs HTTP) needs to match what the client supports, but the server itself is client-agnostic.

How do I report a bug or contribute?

Open an issue or PR on the GitHub repository.