MCP 服务器

MIF MCP Server

Enables AI agents to export, import, validate, and inspect memories in the Memory Interchange Format (MIF), ensuring portability across different memory systems.

README

Memory Interchange Format (MIF)

Your AI agent has 6 months of memories in System A. You want to try System B. Without MIF, you lose everything. With MIF:

pip install mif-tools
mif convert mem0_export.json --to shodh -o memories.mif.json

Done. Your memories are portable.

What is MIF?

A vendor-neutral JSON envelope for AI agent memories. Like vCard for contacts or iCalendar for events — a minimal schema so memories move between providers without data loss.

3 required fields. That's it.

{
  "mif_version": "2.0",
  "memories": [
    {
      "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "content": "User prefers dark mode across all applications",
      "created_at": "2026-01-15T10:30:00Z"
    }
  ]
}

Everything else — memory types, tags, entities, embeddings, knowledge graph, vendor extensions — is optional. Add what you have, ignore what you don't.

Install

# Python
pip install mif-tools              # core (zero dependencies)
pip install mif-tools[validate]    # with JSON Schema validation
pip install mif-tools[mcp]         # with MCP server

# Node.js / TypeScript
npm install @varunshodh/mif-tools

Convert Between Formats

# mem0 → MIF
mif convert mem0_export.json --from mem0 -o memories.mif.json

# MIF → Markdown (Obsidian/Letta style)
mif convert memories.mif.json --to markdown -o memories.md

# Auto-detect source format
mif convert any_memory_file.json -o output.mif.json

# Inspect any memory file
mif inspect memories.json

# Validate MIF document
mif validate memories.mif.json

Python API

from mif import load, dump, convert, MifDocument, Memory

# Load from any format (auto-detects mem0, markdown, generic JSON, MIF)
doc = load(open("mem0_export.json").read())
print(f"{len(doc.memories)} memories loaded")

# Convert between formats in one line
markdown = convert(data, from_format="mem0", to_format="markdown")

# Create memories from scratch
doc = MifDocument(memories=[
    Memory(
        id="123e4567-e89b-12d3-a456-426614174000",
        content="User prefers dark mode",
        created_at="2026-01-15T10:30:00Z",
        memory_type="observation",
        tags=["preferences", "ui"],
    )
])
print(dump(doc))  # MIF v2 JSON

# Deep validation (UUIDs, references, timestamps, embedding dimensions)
from mif import validate_deep
ok, warnings = validate_deep(open("export.mif.json").read())

Add MIF to Your MCP Server (10 lines)

from mif import load, dump

# Export handler
def export_memories(user_id: str) -> str:
    memories = my_storage.get_all(user_id)
    return dump(memories)

# Import handler — auto-detects mem0, markdown, generic JSON, MIF
def import_memories(data: str) -> dict:
    doc = load(data)
    for mem in doc.memories:
        my_storage.save(mem.id, mem.content, mem.created_at)
    return {"memories_imported": len(doc.memories)}

Supported Formats

Format	ID	Auto-detect	Description
MIF v2	`shodh`	`"mif_version"` in JSON	Native format, lossless round-trip
mem0	`mem0`	JSON array with `"memory"` field	mem0 memory exports
CrewAI	`crewai`	JSON array with `"task_description"`	CrewAI LTMSQLiteStorage exports
LangChain	`langchain`	JSON array with `"namespace"` + `"value"`	LangChain/LangMem Item format
Generic JSON	`generic`	JSON array with `"content"` field	Any JSON memory array
Markdown	`markdown`	Starts with `---`	YAML frontmatter (Letta/Obsidian style)

Full Spec

MIF supports optional fields for rich memory data:

Memory types — observation, decision, learning, error, context, conversation, and custom types
Entity references — named entities with type and confidence
Embeddings — model name, dimensions, vector (reuse or regenerate)
Knowledge graph — entities and relationships with confidence scores
Vendor extensions — system-specific metadata preserved on round-trip
Privacy — PII detection and redaction markers

Full specification: spec/mif-v2.md | JSON Schema: schema/mif-v2.schema.json

MCP Server

Expose MIF tools to any MCP-compatible AI client:

pip install mif-tools[mcp]
mif mcp

Tools: export_memories, import_memories, validate_memories, inspect_memories, list_formats

Adapters & Implementations

System	Status	Type
shodh-memory	Production	Built-in HTTP API (`/api/export/mif`, `/api/import/mif`)
mif-tools (PyPI)	Production	Python package with CLI + MCP server
@varunshodh/mif-tools (npm)	Production	TypeScript/Node.js package with CLI
mem0	Adapter ready	Python + npm
CrewAI	Adapter ready	Python + npm
LangChain	Adapter ready	Python + npm
Generic JSON	Adapter ready	Python + npm
Markdown (YAML frontmatter)	Adapter ready	Python + npm

Design Principles

Minimal — 3 required fields. Everything else is optional.
Extensible — Unknown fields and vendor extensions MUST be preserved on round-trip.
Vendor-neutral — The schema doesn't favor any implementation.
Forward-compatible — Importers MUST ignore unknown fields.