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Model Ledger — Claude Code MCP server: model inventory

Model Ledger maps deployed models, their dependencies, and changes over time. Its MCP server lets an AI agent query that inventory.

Install into Claude Code · Platform CLI All methods and platforms ↓
claude mcp add model-ledger -- uvx model-ledger
Open on GitHub

What Model Ledger does

Model Ledger discovers models, heuristics, and ETL across connected platforms, then builds a dependency graph from matching DataNode input and output ports. Each mutation becomes an immutable event, so the ledger can reconstruct its state at a chosen point in time.

The package exposes a Python SDK, CLI, REST API, and an MCP server with eight tools. Storage options include in-memory data, SQLite, JSON, Snowflake, and remote HTTP. The MCP setup uses uvx to launch model-ledger; the README also provides the model-ledger[mcp] package extra for this mode.

What it helps with

  • inventory deployed models
  • trace direct and transitive dependencies
  • reconstruct the ledger at a past point
  • record model changes as events
  • validate models against governance profiles

Example prompts for the agent

  • Show every model that depends on customer_features.
  • Trace the dependency path leading to fraud_alerts.
  • Review the model inventory and list its latest changes.

How to install Model Ledger

Platform CLI

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

uvx runs the command named after the package; if the README names another one, use uvx --from model-ledger <command>

Step by step, with commands for each platform: How to add an MCP server to Claude Code, Codex, Cursor, VS Code, Gemini CLI and more

Questions about Model Ledger

How do I install Model Ledger in Claude Code?

Run claude mcp add model-ledger -- uvx model-ledger.

What does Model Ledger do?

It discovers deployed models, connects their dependencies into a graph, and records mutations in an append-only event log. Agents can query that inventory through MCP.

Which storage backends does Model Ledger support?

It supports in-memory storage, SQLite, JSON, Snowflake, and remote HTTP backends.

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