Context your agents can share and trust

AgentTrunk is a versioned home for skills, prompts, instructions, and documents. Upload a package, test it in staging, and release a reviewed version for any authorized agent to read.

Use AgentTrunk when several agents need the same instructions, when prompts change independently of application code, or when you need to reproduce exactly what an agent read.

Start here

• Connect an agent: Install the CLI, get human approval, and select a workspace.
• Upload context: Publish a skill or prompt to staging.
• Find and read context: Search compact metadata, then fetch only the files you need.
• Review and release: Compare revisions and promote a scope to production.
• Authentication: Connect without sharing a human’s password.
• Integrations: CLI, SDKs, Claude Code, Codex, and portable skills.
• Troubleshooting: Recover from access errors and uncertain writes.

A simple model

Organization: Acme
└── Workspace: Customer support
    └── Context: refund-policy
        ├── policy.md
        └── examples.md
Upload → staging → test the revision → review → production

An organization is your team and its access boundary. A workspace holds context for an agent or use case: customer support, travel planning, or research. The API calls a workspace a trunk.

Inside a workspace, a context is a named package of files, such as refund-policy. Every upload creates an immutable revision. A scope groups context that shares access and release controls. Start with the workspace’s General scope; add scopes only when those boundaries differ.

Staging is for testing changes. Production points to reviewed context. Both can move. Pin the returned revision ID when starting an agent run so all its files come from the same version.

A context set combines pinned sources from multiple authorized scopes or workspaces. It does not bypass source permissions.

What stays in your harness

AgentTrunk stores and serves context. Your harness runs the agent, chooses models, executes tools, evaluates changes, and decides when to request a release. There is no compilation step and no required model.

You can store memory schemas and explicit context files. AgentTrunk is not an automatic memory extractor, a vector database, or an agent execution service. A hosted MCP endpoint is not currently offered; use the CLI or REST API.

Before production

Confirm workspace access, a staging upload, and an exact-version read separately. A successful sign-in alone does not prove these work. Do not upload passwords, API keys, or protected health information. Replacing a file is not erasing its history.

Pricing · Data handling · API contract · Support