Marshal — an agent ledger

A vendor-neutral, open-source ledger for enterprise AI agents. Any format in, any format out, with versions, diffs, portability and audit across every platform.

Live demo · Documentation · Getting started

Marshal reads the agent definitions teams already produce: Databricks bundles, Copilot Studio agents, Bedrock templates, Agentforce metadata, agent code and the open standards. It builds a normalized, versioned record of every agent: what model it asks for, what tools and data it can reach, and who it acts as. Every field says where its value came from, and nothing is guessed.

Status: alpha. Before 1.0 a minor release may change the ledger model, the ingest API or the command line; the changelog lists each such change.

What it does

• Inventory of every agent across platforms, with versions, deployments, and each record's completeness.
• Risk-ranked review: pull requests that change an agent get a comment that lists permission escalations, new write tools and model changes first.
• Drift and freshness: compares what is live with what was shipped, and shows how recently each record was confirmed and by which channel.
• Dependencies: "who uses this tool, this knowledge source, this permission?" across every platform.
• Translation between formats, with a fidelity report computed by reading the result back.
• Portability scores for moving an agent to another platform, from a community-maintained capability matrix.
• No shared secrets: pipelines push records authenticated by their CI provider's OIDC token. Marshal never connects to agent platforms.

How it runs

Pipelines you already run record each agent: a pull request records the proposed definition and gets a comment ranking its changes, a deploy records what was shipped, and an optional scheduled export records what is live in a web designer. See the GitHub Action, Jenkins and Azure DevOps and Deployment.

Formats

Try it

Browse the live demo, or build it yourself from 28 public agents, with nothing to install but uv:

$ uvx --from 'marshal-ledger[server]' marshal demo
$ uvx --from 'marshal-ledger[server]' marshal web --db demo.sqlite

Or pip install 'marshal-ledger[server]', then marshal demo and marshal web --db demo.sqlite. marshal demo downloads the agents' definitions from their public GitHub repositories, pinned to a commit.

Then on your own agents. See Getting started:

$ marshal read path/to/bundle                        # print ledger records
$ marshal collect path/to/bundle --target prod --event shipped
$ marshal ls                                         # every agent, latest version, where it is shipped
$ marshal diff finance/invoice_agent                 # proposed against shipped, ranked by risk
$ marshal status finance/invoice_agent               # shipped vs live per environment, drift, freshness
$ marshal deps "*CheckWeather" --shipped             # who depends on this, and where it is live
$ marshal convert agent.adl.yaml --to agent-spec     # translate, with a fidelity report
$ marshal port finance/invoice_agent --to all        # portability to every platform
$ marshal web                                        # browse the store

collect writes to a local SQLite store (marshal.sqlite, or --db / $MARSHAL_DB). In a shared deployment, pipelines run marshal push or the GitHub Action against the ingest API. Optional scheduled workflows export agents built in a web designer, such as Copilot Studio and Agentforce, and report drift from what was shipped.

Documentation

The documentation is published at marshal-ledger.github.io/marshal.

• Getting started
• Guides: Copilot Studio inventory, pull request review, agents in code, drift, ADK to Agent Spec, audit evidence
• How Marshal compares with platform admin tools, observability, AI gateways, registries and governance platforms
• Design: the problem, architecture, security and network posture, roadmap
• Ledger model v0: records, provenance, version hashing, the version store, risk ranking, freshness
• Conversion and fidelity and Portability
• Formats: Databricks, CloudFormation, Copilot Studio, Agentforce, ADK Agent Config, Vertex AI Agent Engine, Python agent code, ADL, Agent Spec, OASF, Marshal file
• Platform exportability: what each closed platform exposes
• Ingest API, GitHub Action, Jenkins and Azure DevOps and Deployment
• Security review: what is stored, authentication, network, supply chain, retention and audit, for security reviewers

Development

$ pip install -e '.[dev]'
$ python scripts/fetch_fixtures.py     # golden fixtures: real public agent definitions, pinned by commit
$ pytest

See Contributing. Golden fixtures are fetched rather than committed, so each file stays under its upstream license. After changing the model, regenerate the schema with python scripts/generate_schema.py. Report vulnerabilities as described in Security.

License

Marshal is licensed under the Apache License 2.0.