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MCP server · RAG

Roampal

Memory that learns what works.

52Fair

Scored 4 months ago · breakdown

About Roampal

Roampal is an MCP server in the RAG category: memory that learns what works. It has been installed 0 times through Conduid.

Install

Clone
git clone https://github.com/roampal-ai/roampal

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

Roampal

Status Built with Tauri Multi-Provider License

Memory that learns what works. So you can do more of it.

Say it worked. Say it didn't. The AI remembers.

Stop re-explaining yourself every conversation. Roampal remembers outcomes, learns from feedback, and gets smarter over time—all 100% private and local.

85.8% non-adversarial on LoCoMo (1,986 questions). +23 pts over raw ingestion. Absorbs 1,135 poison memories losing only 4 pts. (Paper)


Benchmark Results

LoCoMo dataset (1,986 questions, 5 categories, corrected ground truths). Evaluated with roampal-labs. Dual-graded by local 20B + MiniMax M2.7.

Metric Result
Non-adversarial accuracy (MiniMax-regraded) 85.8%
Overall (all 5 categories) 76.6%
vs raw ingestion baseline +23 pts (76.6% vs 53.0%, p<0.0001)
Poison resilience -4.2 pts after 1,135 adversarial memories
No-memory baseline 6.0% (model has zero LoCoMo knowledge)
Architecture vs model Architecture: +23 pts. Model swap (GPT-4o-mini): 1.5-2.5 pts
  • System learns through natural conversation, not transcript ingestion
  • Absorbs 1,135 poison memories with spoofed trust signals, retaining 72.4% accuracy
  • Wilson scoring hurts retrieval at every stage (p<0.001) — removed from ranking
Config Hit@1 Clean Hit@1 Poison p-value
TagCascade + cosine 27.3% 29.0% baseline
Overlap + cosine 25.8% 28.0% p=0.0003
Pure CE 25.4% 28.4%
TagCascade + Wilson 23.0% 25.0% p<0.0001
  • Cross-encoder: +17.8 Hit@1 over cosine (p<0.0001)
  • Tag routing (two-lane): +6.1 Hit@1 clean, +7.5 poison (p<0.0001)
  • Wilson: -4.3 Hit@1 in every configuration
  • Nursery slot: zero benefit (p=1.0)

Full methodology in roampal-labs


Quick Start

  1. Download from roampal.ai and extract
  2. Install Ollama or LM Studio
  3. Right-click Roampal.exeRun as administrator
  4. Download a model in the UI → Start chatting!

Your AI starts learning about you immediately.


Table of Contents


Key Features

Memory That Learns

  • Outcome tracking: Scores every result (+0.2 worked, -0.3 failed)
  • Smart promotion: Good advice becomes permanent, bad advice auto-deletes
  • Cross-conversation: Recalls from ALL past chats

Your Knowledge Base

  • Memory Bank: Permanent storage of preferences, identity, goals
  • Books: Upload .txt/.md docs as searchable reference
  • Pattern recognition: Detects what works across conversations

Privacy First

  • 100% local: All data on your machine
  • Works offline: No internet after model download
  • No telemetry: Your data never leaves your computer

MCP Integration

Connect Roampal to Claude Desktop, Cursor, and other MCP-compatible tools.

Settings → Integrations → Connect → Restart your tool

7 tools available: search_memory, add_to_memory_bank, update_memory, archive_memory, get_context_insights, record_response, score_memories

Full MCP documentation →


Architecture

┌─────────────────────────────────────────────────────────┐
│                    5-TIER MEMORY                        │
├─────────────┬─────────────┬─────────────┬──────────────┤
│   Books     │   Working   │   History   │   Patterns   │
│ (permanent) │   (24h)     │  (30 days)  │  (permanent) │
├─────────────┴─────────────┴─────────────┴──────────────┤
│                    Memory Bank                          │
│            (permanent user identity/prefs)              │
└─────────────────────────────────────────────────────────┘

Core Technology:

  • TagCascade Retrieval: Tag-routed search + cross-encoder reranking (ONNX)
  • Outcome-Based Learning: Memories adapt based on feedback
  • Sidecar LLM: Background model summarizes exchanges, extracts facts and tags

Architecture deep-dive →


Supported Models

Works with any tool-calling model via Ollama or LM Studio:

Model Provider Parameters
Llama 3.x Meta 3B - 70B
Qwen 2.5 Alibaba 3B - 72B
Mistral/Mixtral Mistral AI 7B - 8x22B
GPT-OSS OpenAI (Apache 2.0) 20B - 120B

Documentation

Document Description
Architecture 5-tier memory, knowledge graphs, technical deep-dive
Benchmarks LoCoMo evaluation, TagCascade results
Release Notes Latest (v0.3.2): chat-path latency fixes, fact dedup, universal provider error handling, shared-DB timestamp tolerance, TagCascade filter correctness

Important Notices

AI Safety: LLMs may generate incorrect information. Always verify critical information. Don't rely on AI for medical, legal, or financial advice.

Model Licenses: Downloaded models (Llama, Qwen, etc.) have their own licenses. Review before commercial use.


Support


Pricing

Free & open-source (Apache 2.0 License)

  • Build from source → completely free
  • Pre-built executable: $19.99 one-time (saves hours of setup)
  • Zero telemetry, full data ownership

Made with love for people who want AI that actually remembers

README mirrored from the source repository 4 months ago. The original is authoritative.

Questions

About Roampal

How do I install Roampal?

Run git clone https://github.com/roampal-ai/roampal, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Roampal safe to use with an AI agent?

Its trust score is 52 out of 100 (fair). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Roampal still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.