Model Ledger

Name: Model Ledger
Author: block

by blockversion 0.7.13i★ –iRuns on your computer

Registry nameio.github.block/model-ledger

Install

Overview

Description from the maker (original English)

Model inventory and governance: trace deployed models and their dependencies as an append-only log

PopNx MCP’s three pillars

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

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

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: Accounting, finance & tax

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?

ClaudeClaude CodeCursorVS CodeChatGPT

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": {
    "model-ledger": {
      "command": "uvx",
      "args": [
        "model-ledger",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add model-ledger -- uvx model-ledger mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "model-ledger": {
      "command": "uvx",
      "args": [
        "model-ledger",
        "mcp"
      ]
    }
  }
}

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": {
    "model-ledger": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "model-ledger",
        "mcp"
      ]
    }
  }
}

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account block, 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 Accounting, finance & taxi

More stars than 0% of the other 1720 servers in this category
Published to the registry more recently than 27% of the other 1720 servers in this category
Basic checks equal to or better than 100% of the other 1720 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 Model Ledger 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 (0.7.13) reached the registry 4 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: Finance Toolkit, SolidInvoice, Korea Tax Calculator

Alternatives

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

Finance Toolkit

by JerBouma

500+ transparent financial methods calculated from raw statements, not third-party endpoints.

Computer or cloud★ 5,496MITUpdated yesterday

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SolidInvoice

by SolidInvoice

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Runs in the cloud★ 981MITUpdated 7 days ago

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Korea Tax Calculator

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Runs on your computer★ 97MITUpdated today

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.

model-ledger

git for models — know what models you have deployed, where they run, what they depend on, and what changed.

📖 [Documentation](https://block.github.io/model-ledger/) · Quickstart · Concepts · Governance

model-ledger is a model inventory for any organization with deployed models. It discovers models, heuristic rules, and ETL across your platforms, maps the dependency graph automatically, and records every change as an immutable event. Unlike registries tied to a single platform (MLflow, SageMaker, W&B), it spans all of them — as one connected graph — and it's built to be driven by AI agents through a native MCP server.

Benchmarked at production scale: full inventory reconstruction over a ledger of 28.8k models and 212k events runs in under a second (CHANGELOG, v0.7.4).

Install

pip install model-ledger

The graph builds itself

Every model is a DataNode with typed input and output ports. When an output port name matches an input port name, connect() creates the dependency edge — no hand-wiring.

from model_ledger import Ledger, DataNode

ledger = Ledger()

ledger.add([ DataNode("segmentation", platform="etl", outputs=["customer_segments"]), DataNode("fraud_scorer", platform="ml", inputs=["customer_segments"], outputs=["risk_scores"]), DataNode("fraud_alerts", platform="alerting", inputs=["risk_scores"]), ]) ledger.connect()

ledger.trace("fraud_alerts")

['segmentation', 'fraud_scorer', 'fraud_alerts']

Every mutation is recorded as an immutable Snapshot — an append-only event log that gives you full history and point-in-time reconstruction, because nothing is overwritten.

Talk to your inventory

The MCP server is a first-class surface — point Claude (or any MCP agent) at it:

pip install "model-ledger[mcp]"

claude mcp add model-ledger -- model-ledger mcp --demo

You: if we deprecate customer_features, what breaks?

Claude: 3 models consume it directly, 2 more transitively.

Documentation

Everything lives at [block.github.io/model-ledger](https://block.github.io/model-ledger/) — and it can't drift, because the API reference is generated from source and every example runs in CI:

[Quickstart](https://block.github.io/model-ledger/quickstart/) — install to your first dependency trace in 60 seconds
[Concepts](https://block.github.io/model-ledger/concepts/) — DataNode, Snapshot, and Composite, in three ideas
[Agents (MCP)](https://block.github.io/model-ledger/guides/agents/) — the eight-tool agent surface, with a worked transcript
[Connectors](https://block.github.io/model-ledger/guides/connectors/) — discover from SQL, REST, GitHub, or your own platform
[Backends](https://block.github.io/model-ledger/guides/backends/) — in-memory, SQLite, JSON, Snowflake, or remote HTTP
[Governance](https://block.github.io/model-ledger/governance/) — how the primitives map to SR 11‑7/SR 26‑2, the EU AI Act, and NIST AI RMF
[API reference](https://block.github.io/model-ledger/reference/) — generated from the source

Architecture

flowchart LR

subgraph Sources C1[SQL / REST / GitHub / Prefect connectors] end subgraph Core L[Ledger append-only event log, point-in-time reconstruction] G[Dependency graph] V[Compliance profiles SR 11-7/SR 26-2 · EU AI Act · NIST AI RMF] end subgraph Surfaces S1[Python SDK] S2[CLI] S3[REST API] S4[MCP server · 8 tools] end B1[(in-memory · SQLite · JSON · Snowflake · remote HTTP)] C1 --> L L --> G L --> V L --- B1 S1 --> L S2 --> L S3 --> L S4 --> L

For organizations

The OSS core handles discovery, graph building, change tracking, storage, the agent protocol, and compliance validation — the SR 11‑7/SR 26‑2, EU AI Act Annex IV, and NIST AI RMF profiles ship in model_ledger.validate. Your internal package provides only the thin layer on top: connector configs, custom connectors for internal platforms, and credentials. Thin config, not reimplemented logic.

Contributing

See CONTRIBUTING.md. All commits require DCO sign-off.

Security

See SECURITY.md for how to report vulnerabilities privately.

License

Apache-2.0. See LICENSE.

Created and maintained by Vignesh Narayanaswamy at Block.

Model Ledger

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Accounting, finance & taxi

Common questions

Alternatives

Finance Toolkit

SolidInvoice

Korea Tax Calculator

README from the maker

model-ledger

Install

The graph builds itself

['segmentation', 'fraud_scorer', 'fraud_alerts']

Talk to your inventory

Documentation

Architecture

For organizations

Contributing

Security

License