AgentIndex icon
AgentIndex
Waggle-mcp logo
Waggle-mcp
★ 44
vs
rlm-claude logo
rlm-claude
★ 39

Waggle-mcp vs rlm-claude

Waggle-mcp: Waggle-mcp provides AI agents with a persistent, graph-backed memory that remembers decisions, reasons, and contradictions across sessions, overcoming the limitations of short context windows. It acts as a local-first memory layer for MCP-compatible AI clients, allowing for rich, structured context retrieval instead of simple text snippets.; rlm-claude: RLM is an MCP server designed to provide Claude Code with persistent memory, preventing loss of conversation history and context after `/compact` operations. It offers advanced memory management features including insights, chunking, and intelligent retention, enabling more productive and context-aware AI interactions.

01

TL;DR

Waggle-mcp logo
Waggle-mcpMemory & Context · ★ 44

Maintaining long-term conversational memory for AI coding assistants across development sessions.

Read Waggle-mcp full review →
rlm-claude logo
rlm-claudeMemory & Context · ★ 39

Preventing context and decision loss during long Claude Code development sessions.

Read rlm-claude full review →
02

Side-by-Side Comparison

Field
Waggle-mcp logoWaggle-mcp
rlm-claude logorlm-claude
Category
Memory & Context
Memory & Context
Stars
★ 44
★ 39
License
Apache-2.0
MIT
Install Command
pipx install waggle-mcp && waggle-mcp setup --yes
pip install mcp-rlm-server[all]
Updated
1w ago
2w ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Persistent Memory, Knowledge Graph, AI Agent Memory
Persistent Memory, Claude Code Integration, Context Management
03

Features

Waggle-mcp logoWaggle-mcp
01Persistent graph memory with SQLite backend by default, with optional Neo4j support.
02Integrates as an MCP server with automatic memory hooks for various AI clients like Claude, Cursor, and Gemini CLI.
03Recursive context assembly to provide compact, high-signal context packs, optimizing token usage.
04Stores relationships between facts, decisions, and contradictions, enabling temporal queries, diffs, and conflict resolution.
05Local embeddings with a deterministic offline fallback, ensuring privacy and local operation.
rlm-claude logorlm-claude
01Automatic snapshot saving before context loss during `/compact`.
02Dual memory systems: 'Insights' for key decisions/facts and 'Chunks' for full conversation segments.
03Hybrid search combining BM25 keyword matching and semantic cosine similarity.
04Smart retention lifecycle with active, archive, and purge zones, and immunity for critical data.
05Multi-project and multi-domain organization for memory and search filtering.
04

Use Cases

Waggle-mcp logoWaggle-mcp
↳Maintaining long-term conversational memory for AI coding assistants across development sessions.
↳Retrieving past decisions, constraints, and preferences to inform current AI agent actions.
↳Tracking changes and resolving contradictions in evolving project requirements or design choices.
↳Exporting and sharing AI agent memory snapshots for collaboration or migration between machines/sessions.
↳Debugging AI agent reasoning and understanding context by inspecting the underlying knowledge graph via Graph Studio.
rlm-claude logorlm-claude
↳Preventing context and decision loss during long Claude Code development sessions.
↳Efficiently recalling past project details, architectural decisions, and technical findings.
↳Organizing and searching through AI-generated knowledge across different projects and domains.
↳Revisiting debug sessions and past solutions for problem-solving and code refactoring.
↳Maintaining universal rules and preferences that apply across all AI interactions.
FAQ

FAQ

What is the difference between Waggle-mcp and rlm-claude?
Both Waggle-mcp and rlm-claude are in the Memory & Context category. Waggle-mcp has 44 stars, while rlm-claude has 39 stars.
Which is better, Waggle-mcp or rlm-claude?
The best choice depends on your use case. Choose Waggle-mcp if Maintaining long-term conversational memory for AI coding assistants across development sessions., and rlm-claude if Preventing context and decision loss during long Claude Code development sessions..
Is Waggle-mcp free or open source?
Yes, Waggle-mcp is open source on GitHub (Apache-2.0).
Is rlm-claude free or open source?
Yes, rlm-claude is open source on GitHub (MIT).
Cloud Infrastructure
Ad

Deploy on DigitalOcean

Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.

Claim $200 Free Credit
→

Related

Alternatives to Waggle-mcp →Alternatives to rlm-claude →Waggle-mcp details →rlm-claude details →