~/.ghostkeep/ (or $GHOSTKEEP_DIR)
├── facts.json        # Canonical active, conflicted, and superseded facts
├── conflicts.json    # Pending & resolved cross-agent contradiction queue
└── provenance.jsonl  # Append-only immutable event ledger (audit trail)

                     ┌───────────────────────────┐
                     │   Claude Desktop / Code   │
                     ├───────────────────────────┤
                     │     Cursor / Windsurf     │
                     ├───────────────────────────┤
                     │   Custom Agents / Scripts │
                     └─────────────┬─────────────┘
                                   │ (MCP / Python)
                                   ▼
                     ┌───────────────────────────┐
                     │         GHOSTKEEP         │
                     │  MemoryStore & MCP Server │
                     └─────────────┬─────────────┘
                                   │
              ┌────────────────────┼────────────────────┐
              ▼                    ▼                    ▼
      ┌───────────────┐    ┌───────────────┐    ┌────────────────┐
      │  facts.json   │    │conflicts.json │    │provenance.jsonl│
      │ (Source Truth)│    │(Contradictions│    │(Audit Ledger)  │
      └───────────────┘    └───────────────┘    └────────────────┘

git clone https://github.com/Akshu24Tech/ghostkeep.git
cd ghostkeep
pip install -e .

pip install -r requirements.txt

{
  "mcpServers": {
    "ghostkeep": {
      "command": "python",
      "args": ["-m", "ghostkeep.server"],
      "env": {
        "GHOSTKEEP_DIR": "~/.ghostkeep"
      }
    }
  }
}

{
  "mcpServers": {
    "ghostkeep": {
      "command": "python",
      "args": ["path/to/ghostkeep/server.py"],
      "env": {
        "GHOSTKEEP_DIR": "~/.ghostkeep"
      }
    }
  }
}

{
  "mcpServers": {
    "ghostkeep": {
      "command": "python",
      "args": ["path/to/ghostkeep/server.py"]
    }
  }
}

from ghostkeep import MemoryStore

store = MemoryStore("./my_memory")

# 1. Add memories from different agents
f1 = store.add_memory(
    content="User prefers Python for data engineering projects",
    source_agent="claude-code",
    source_session_id="session-2026-09-18",
    confidence=0.95,
    tags=["preferences", "python"]
)

# 2. Search memories
results = store.search_memory("Python preferences", min_confidence=0.5)
for fact in results:
    print(f"[{fact['source_agent']}] {fact['content']} (confidence: {fact['confidence']})")

# 3. Inspect provenance and audit chain
prov = store.get_provenance(f1["id"])
print("History of events:", prov["events"])

# 4. Check and resolve conflicts
conflicts = store.list_conflicts()
for conflict in conflicts:
    print(f"Conflict detected between {conflict['fact_id_a']} and {conflict['fact_id_b']}")
    store.resolve_conflict(conflict["id"], resolution="keep_a", resolved_by="human-reviewer")

python -m unittest tests/test_store.py
# or if pytest is installed:
pytest