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Mif Tools

by varun29ankuSversion 0.2.1i★ –iRuns on your computer
Registry nameio.github.varun29ankuS/mif-tools

Install

Overview

Description from the maker (original English)

Convert, validate, and inspect AI agent memories across formats

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "mif-tools": {
      "command": "uvx",
      "args": [
        "mif-tools"
      ]
    }
  }
}

Run this in your terminal

claude mcp add mif-tools -- uvx mif-tools

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "mif-tools": {
      "command": "uvx",
      "args": [
        "mif-tools"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "mif-tools": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mif-tools"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account varun29ankuS, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32700 servers in this category
  • Published to the registry more recently than 3% of the other 32700 servers in this category
  • Basic checks equal to or better than 100% of the other 32700 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Mif Tools safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 8 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Agent Data Tools: Utilities

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by formulahendry

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

FormatIDAuto-detectDescription
MIF v2shodh"mif_version" in JSONNative format, lossless round-trip
mem0mem0JSON array with "memory" fieldmem0 memory exports
CrewAIcrewaiJSON array with "task_description"CrewAI LTMSQLiteStorage exports
LangChainlangchainJSON array with "namespace" + "value"LangChain/LangMem Item format
Generic JSONgenericJSON array with "content" fieldAny JSON memory array
MarkdownmarkdownStarts 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

SystemStatusType
shodh-memoryProductionBuilt-in HTTP API (/api/export/mif, /api/import/mif)
mif-tools (PyPI)ProductionPython package with CLI + MCP server
@varunshodh/mif-tools (npm)ProductionTypeScript/Node.js package with CLI
mem0Adapter readyPython + npm
CrewAIAdapter readyPython + npm
LangChainAdapter readyPython + npm
Generic JSONAdapter readyPython + npm
Markdown (YAML frontmatter)Adapter readyPython + npm

Design Principles

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

Contributing

We welcome adapter implementations for any memory system. See CONTRIBUTING.md.

Related

License

Apache 2.0

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