Tell your agent what to build. Avowgate keeps a checklist of everything it promised, ties each item to a test, and will not call the work finished until the tests pass. You see what holds up, what does not, and what is running in production. That is how you decide what to trust.
Copy this into Claude Code or any AI coding agent. It connects to Avowgate, sets up your first product, and follows the gate from then on. Nothing to install.
Set up Avowgate for this project, so that nothing counts as done until tests prove it. 1. Ask me for my Avowgate access token (I create it under Settings in the app at https://avowgate.com/app/). Then connect, replacing TOKEN with the token I give you: claude mcp add --transport http avowgate https://avowgate.com/api/v1/mcp --header "Authorization: Bearer TOKEN" If you are not Claude Code, add an MCP server with that URL and that Authorization header. Tell me if a restart is needed before the tools appear. 2. Call at_list_products. If this project has no product yet, call at_create_product with a short code and a name. 3. Call at_list_packs, tell me which starter packs fit this project, and apply the ones I choose with at_apply_pack. 4. For each requirement, write a test, then record it with at_create_test and link it with at_link_spec_test. 5. Run the tests and report the results with at_report_results, including the commit. 6. Before you tell me anything is done, call at_check_gate. If it is blocked, fix what it lists. Never say it is done while the gate is blocked.
Works with Claude Code and any tool that supports MCP over HTTP. You need an account to create the access token the agent asks for.
A simple loop that your agent follows and you can audit.
Before coding starts, the agent writes your request down in plain words.
Your request becomes specific statements that either hold or do not.
Each promise points at the tests that prove it. A promise that nothing tests shows as open.
The work cannot be closed until every promise has passing proof.
Agents are fast and confident. Avowgate is how you know what to trust.
The verdict comes from test results tied to a specific commit, not from the agent’s summary.
Packs add the checks that are easy to forget: web security, payments, accounts and passwords, safe delivery.
Record which commit is running, so the verdict describes production and not just a branch.
Accepting a known risk is a human action with a record, never something an agent can do for itself.
Every request, promise, result and sign-off is kept, so you can see how a decision was made.
Command line, an MCP server and hooks let agents report as they work.
Short answers about what Avowgate does and how an agent uses it. Agents can read the same steps at /agents/.
Avowgate is a hosted service that keeps a checklist of what your AI coding agent promised to do, links each item to a test, and refuses to call the work done until those tests pass. The answer is a gate that reads pass or blocked, with the reasons.
An agent summary is a claim. Avowgate replaces it with a verdict built from test results tied to a specific commit. A promise with no test shows as open, and the gate stays blocked until every promise has passing proof or a named person accepts the risk.
Create an access token under Settings in the app, then add Avowgate as an MCP server over HTTP. In Claude Code the command is claude mcp add --transport http avowgate https://avowgate.com/api/v1/mcp --header "Authorization: Bearer YOUR_TOKEN". Any client that supports MCP over HTTP can use the same address and header. Nothing needs to be installed.
Claude Code and any other agent or tool that can talk to an MCP server over HTTP. There is also a command line tool and hooks for setups that do not use MCP.
The gate blocks closing a task while any promise is untested, failing, waiting for a person to sign off, or covered only by a test that has not run on the current commit. It passes when every promise has passing proof for the commit, or an accepted risk recorded by a person.
An agent can read everything, write requirements, link tests, and report results and findings. It cannot sign off a risk, dismiss a finding, promote a gate rule or retire a test. Those decisions belong to a person and are recorded with their name.
It stores the requests, requirements, test names, test results, commit identifiers, deployment records and notes that you or your agent send. It does not run your tests or fetch your code. It does not send your content to AI services and does not use it to train AI models.
Any software project where an AI agent writes code and a person needs to know what to trust. Starter packs add the checks that are easy to forget: web security, payments, accounts and passwords, and safe delivery.
Yes. The home page has a read-only live demo that needs no account. Sign-up is currently by early access: leave your email on the home page and you will be written to when there is room.
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