nemp 0.1.0

Persistent local memory for AI agents. Remembers everything.

nemp

Persistent local memory for AI agents. Remembers everything.

Zero dependencies. Pure Python. One-line integration.

from nemp import recall_all

memories = recall_all("/app")
# {"framework": "FastAPI", "database": "MongoDB", "auth": "Google OAuth", ...}

Why

AI agents forget everything between sessions. Every time you start a new session, you re-explain your stack, your decisions, your preferences.

Nemp fixes this. Agents remember across sessions, automatically.

Install

pip install nemp

Quick Start

from nemp import init, save, recall, context

# Auto-detect project stack
init("/path/to/project")

# Save a decision
save("database", "MongoDB with 3 collections: users, todos, categories",
     tags=["stack", "database"], agent_id="architect")

# Recall by keyword (with semantic expansion)
results = recall("db")  # finds "database" memories too

# Get full context for agent injection
ctx = context()

Emergent Integration (1 line)

# In Emergent's agent startup:
from nemp import inject_context

prompt = inject_context("/app", "You are a coding agent...")
agent = Agent(system_prompt=prompt)
# Agent now knows everything from all previous sessions

7 Functions

Function	Description
init(path)	Auto-detect stack, save as memories
save(key, value, tags, agent_id)	Save a memory (auto-compresses)
recall(keyword)	Search with semantic expansion
list_memories()	List all memories
forget(key)	Delete a memory
context()	Full context as prompt-ready string
log(thought, agent_id)	Log agent thoughts

Bonus:

• recall_all(path) → Dict of all memories (Emergent one-liner)
• inject_context(path, prompt) → Prepend context to system prompt

How It Works

Memories stored in .nemp/ directory as JSON:

project/
└── .nemp/
    ├── memories.json    # All memories
    ├── MEMORY.md        # Auto-generated index
    └── access.log       # Audit trail

Same format as the MCP server. Memories saved by Claude Code via MCP are readable by Emergent via Python, and vice versa.

Schema

[
  {
    "key": "database",
    "value": "MongoDB with 3 collections",
    "tags": ["stack", "database"],
    "timestamp": "2026-02-12T10:30:00.000Z",
    "agent_id": "architect",
    "source": "manual",
    "compressed": false
  }
]

Links

• Website: nemp.dev
• MCP Server: npm
• Claude Code Plugin: GitHub
• Python Package: GitHub

License

MIT