roampal-core

Persistent memory for Claude Code with outcome-based learning. Tracks what helped vs failed, auto-injects context via hooks.

Roampal — Outcome-Based Persistent Memory MCP Server


Why?

AI coding assistants forget everything between sessions. You explain your architecture, your preferences, your conventions — again. When they give bad advice, there's no mechanism to learn from it.

Roampal is an MCP server that gives your AI persistent, outcome-based memory across every session. Good advice gets promoted. Bad advice gets demoted. Your AI learns what works and what doesn't — automatically, with zero workflow changes.


Quick Start

pip install roampal
roampal init

Auto-detects installed tools. Restart your editor and start chatting.

Target a specific tool: roampal init --claude-code or roampal init --opencode

The core loop is identical — both platforms inject context, capture exchanges, and score outcomes. The delivery mechanism differs:

Claude CodeOpenCode
Context injectionHooks (stdout)Plugin (system prompt)
Exchange captureStop hookPlugin session.idle event
ScoringMain LLM via score_memories toolIndependent sidecar (your chosen model > Zen free)
Self-healingHooks auto-restart server on failurePlugin auto-restarts server on failure

Claude Code prompts the main LLM to score each exchange via the score_memories tool. OpenCode uses an independent sidecar — a separate API call that reviews the exchange transcript as a third party, removing self-assessment bias. During roampal init or roampal sidecar setup, Roampal detects local models (Ollama, LM Studio, etc.) and lets you choose a scoring model. If configured, these take priority (Zen is skipped for privacy). A cheap or local model works great — scoring doesn't need a powerful model. Defaults to Zen free models (remote, best-effort) if you skip setup.

How It Works

When you type a message, Roampal automatically injects relevant context before your AI sees it:

You type:

fix the auth bug

Your AI sees:

═══ KNOWN CONTEXT ═══
• JWT refresh pattern fixed auth loop [id:patterns_a1b2] (3d, 90% proven, patterns)
• User prefers: never stage git changes [id:mb_c3d4] (memory_bank)
═══ END CONTEXT ═══

fix the auth bug

No manual calls. No workflow changes. It just works.

The Loop

  1. You type a message
  2. Roampal injects relevant context automatically (hooks in Claude Code, plugin in OpenCode)
  3. AI responds with full awareness of your history, preferences, and what worked before
  4. Outcome scored — good advice gets promoted, bad advice gets demoted
  5. Repeat — the system gets smarter every exchange

Five Memory Collections

CollectionPurposeLifetime
workingCurrent session context24h — promotes if useful, deleted otherwise
historyPast conversations30 days, outcome-scored
patternsProven solutionsPersistent while useful, promoted from history
memory_bankIdentity, preferences, goalsPermanent
booksUploaded reference docsPermanent

Commands

roampal init                # Auto-detect and configure installed tools
roampal init --claude-code  # Configure Claude Code explicitly
roampal init --opencode     # Configure OpenCode explicitly
roampal init --no-input     # Non-interactive setup (CI/scripts)
roampal start               # Start the HTTP server manually
roampal stop                # Stop the HTTP server
roampal status              # Check if server is running
roampal status --json       # Machine-readable status (for scripting)
roampal stats               # View memory statistics
roampal stats --json        # Machine-readable statistics (for scripting)
roampal doctor              # Diagnose installation issues
roampal summarize           # Summarize long memories (retroactive cleanup)
roampal score               # Score the last exchange (manual/testing)
roampal context             # Output recent exchange context
roampal ingest <file>       # Add documents to books collection
roampal books               # List all ingested books
roampal remove <title>      # Remove a book by title
roampal sidecar status      # Check scoring model configuration (OpenCode)
roampal sidecar setup       # Configure scoring model (OpenCode)
roampal sidecar disable     # Remove scoring model configuration (OpenCode)

MCP Tools

Your AI gets these memory tools:

ToolDescriptionPlatforms
search_memoryDeep search across all collectionsBoth
add_to_memory_bankStore permanent facts (identity, preferences, goals)Both
update_memoryCorrect or update existing memoriesBoth
delete_memoryRemove outdated infoBoth
score_memoriesScore previous exchange outcomesBoth (see note)
record_responseStore key takeaways from significant exchangesBoth

How scoring works: Claude Code's hooks prompt the main LLM to call score_memories every turn. OpenCode uses an independent sidecar that scores silently in the background — the model never sees a scoring prompt and never calls score_memories. The tool is registered for both platforms but OpenCode's plugin handles all scoring independently. If the sidecar fails completely, the model is prompted to suggest roampal sidecar setup. Choose your scoring model during roampal init or via roampal sidecar setup.

What's Different?

Without RoampalWith Roampal
Forgets everything between sessionsRemembers you, your preferences, what worked
You repeat context every timeContext injected automatically
No learning from mistakesOutcomes tracked — bad advice gets demoted
No document memoryIngest docs, searchable forever

Benchmarks

Tested across 10 adversarial scenarios designed to trick similarity search (200 total tests):

ConditionTop-1 Accuracy
RAG baseline (vector search only)10%
+ Cross-encoder reranking20%
Full Roampal (outcomes + reranking)10% → 60% at maturity

Outcome learning provides a 5x improvement over reranking alone (+50 pts vs +10 pts). Roampal vs plain vector DB: 40% vs 0% accuracy on adversarial queries (p=0.000135).

Full benchmark data: dev/benchmarks/results/

How Roampal Compares

FeatureRoampal Core.cursorrules / CLAUDE.mdMem0
Learns from outcomesYes — bad advice demoted, good advice promotedNoNo
Zero-config context injectionYes — injected automatically (hooks or plugin)Manual file editingAPI calls required
Works across sessionsYes — 5 memory collections with promotionPer-project static filesYes
Fully local / privateYes — all data on your machineYesCloud or self-hosted
Open sourceApache 2.0N/AApache 2.0
┌─────────────────────────────────────────────────────────┐
│  pip install roampal && roampal init                    │
│    Claude Code: hooks + MCP → ~/.claude/                │
│    OpenCode:    plugin + MCP → ~/.config/opencode/      │
└─────────────────────────────────────────────────────────┘
                         │
                         ▼
┌─────────────────────────────────────────────────────────┐
│  HTTP Hook Server (port 27182)                          │
│    Auto-started on first use, self-heals on failure     │
│    Manual control: roampal start / roampal stop         │
└─────────────────────────────────────────────────────────┘
                         │
                         ▼
┌─────────────────────────────────────────────────────────┐
│  User types message                                     │
│    → Hook/plugin calls HTTP server for context          │
│    → AI sees relevant memories, responds                │
│    → Exchange stored, scored (hooks or sidecar)         │
└─────────────────────────────────────────────────────────┘
                         │
                         ▼
┌─────────────────────────────────────────────────────────┐
│  Single-Writer Backend                                  │
│    FastAPI → UnifiedMemorySystem → ChromaDB             │
│    All clients share one server, isolated by session    │
└─────────────────────────────────────────────────────────┘

See dev/docs/ for full technical details.

Requirements

  • Python 3.10+
  • One of: Claude Code or OpenCode
  • Platforms: Windows, macOS, Linux (primarily developed and tested on Windows)

Troubleshooting

  • Restart Claude Code (hooks load on startup)
  • Check HTTP server: curl http://127.0.0.1:27182/api/health
  • Verify ~/.claude.json has the roampal-core MCP entry with correct Python path
  • Check Claude Code output panel for MCP errors
  • Make sure you ran roampal init --opencode
  • Check that the server auto-started: curl http://127.0.0.1:27182/api/health
  • If not, start it manually: roampal start

This is expected. Roampal has self-healing -- if the HTTP server stops responding, it is automatically restarted and retried.

Still stuck? Ask your AI for help — it can read logs and debug Roampal issues directly.

Support

Roampal Core is completely free and open source.

License

Apache 2.0

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