# Audit Log — builder-mcp (Track A)

## Initial User Request
**Timestamp**: 2026-08-03T15:30:00Z
**User Input**: "Hey, make us a branch called builder. Then, help us build out this builder mcp - we are in the inception phase. Here is what we've worked out so far. --- Summary of starter thoughts:

chat --> request --> mcp

Inputs

* blueprint
* guardrails
* authentication for literal builder mcp
* authentication for future user of blueprint

Function

* Search available blueprints
* Create a repo from a template
   * Whose repo?
* Execute deployment
* Health check on deployment
* Restart a deployment
* Modify a deployment
* Playwright MCP

Outputs

* API calls

Features

* Lots of UI for checkbox input, multiple choice, confirm buttons
* Export"
**AI Response**: Created branch `builder` from d8bbf12. Loaded AI-DLC core workflow and inception rules from the cloned awslabs/aidlc-workflows repo. Loaded workshop context: CLAUDE.md, product proposal (five planes, D1–D8 decisions), participant brief (Track A scope, seven demo beats). Began Requirements Analysis; generated requirement-verification-questions.md and stopped at the answer gate.
**Context**: Inception phase, Requirements Analysis, Track A (Cornell Builder MCP)

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## Requirements Answers Received
**Timestamp**: 2026-08-03T17:10:00Z
**User Input**: "Pull the latest versions of this and the aws ai dlc repos from main, get branch updated, and then go. Q1 - A. Q2.    - HTTP MCP, start local, end deployed on AWS agent core mcp gateway by end of day verified and snazzy.  use my aws cli    Q3 - All six tools TODAY.   Q4.   Q5. -- skip. Q6.      A, I think  Q7. A, I think  Q8.  A - whatever is particualrly AWS friendly . I have python and fastapi on this computer. You can access git from my powershell with 'gitbash' command. Q9 --- a spec - A.     What purposes are the exports for..... 1. validation by another coder.  2. someone who needs a narrative of the business logic. 3. security/authentication check.  4. transfer - ie. help someone else build this elsewhere. 5. how to use this as-is. 6. lower priority: a faculty member is leaving cornell; how do they transfer this elsewhere? ...... We should probably have a system for releases, and release notes. ---- Work on this for now and we will ping you with more architectural thoughts. --- Give us options for versioning, releases, and backups and recovery.   Two example cases: a. if you build an mcp from a blueprint, all that code still lives somewehere. If you build a project knowledgebase from a blueprint and lose it, that data is gone for ever. oops."
**AI Response**: Rebased builder onto origin/main 416891b (AI-DLC rules now vendored in-repo); aidlc-workflows already current. Recorded answers in requirement-verification-questions.md (Q4 unanswered — proceeding on recommendation A, flagged for confirmation). Generated requirements.md and versioning-releases-and-recovery-options.md. Proceeding to Construction: six-tool FastMCP server, local streamable HTTP now, Bedrock AgentCore deployment by end of day.
**Context**: Requirements Analysis complete → Construction begins (compressed workflow per mob's "go" and one-day deadline)

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## Architectural Direction + Constraint
**Timestamp**: 2026-08-03T18:40:00Z
**User Input**: "We will host builder mcp on aws agent core.  Ask us productionizing questions too where relevant

You are not allowed to change the hello world blueprint.yaml substantively. Another team relies on it being a shared standard."
**AI Response**: AgentCore hosting confirmed (was Q2's answer; now firm). blueprints/hello-world/blueprint.yaml frozen as the cross-team manifest standard — noted that the only post-circulation edit was a comment reword required to keep validate_stacks.py's text scan from misreading it (schema and values untouched). Generated construction/agentcore-productionizing-questions.md (P1–P6: topology, inbound auth, account/tags, GitHub credential, IaC debt, observability) and the AgentCore Dockerfile. AWS SSO token found expired; deploy blocked until `aws sso login`.
**Context**: Construction — AgentCore deployment planning

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## Deployment Handoff + Spec-Driven Docs Directive
**Timestamp**: 2026-08-03T20:05:00Z
**User Input**: "Here is the guide for deployment, by the way. We're going to verify everything locally and then pause before deployment, and my colleague who has the right account will take over and deploy on their aws account instead. Actually, sounds like my colleague marty has a whole system - so as long as we get this to github, he'll take it the rest of the way. But here are the steps.   https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-mcp.html   ---- Before we proceed, please utilize best practices of spec driven development, using a contract doc system and clear project knowledge doc, so we don't rely on one chat long term. Encode as much knowledge as you can from our session, in a clear searchable format, to help future agents."
**AI Response**: Local verification completed: 22 tests green, HTTP smoke test green in stateful and stateless modes, linux/arm64 image builds, infra/builder-mcp.yml lints clean and is registered as deployed_by: manual. No deploy from this machine. Wrote SPEC.md (contracts C1–C7), aidlc-docs/PROJECT-KNOWLEDGE.md (decision log DECISION-01..17, gotchas, glossary), deploy/HANDOFF.md (Marty's runbook). Pushed to fork for handoff.
**Context**: Construction complete → Operations handoff

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## Course Correction: Pipeline-Native Deployment
**Timestamp**: 2026-08-03T21:10:00Z
**User Input**: "Hey is that overkill to make a dockerfile right now? Love what you're doing, but might not need it - can't quite tell. This repo is complex. Review the current state of the github repo, particuarly the intended deployment method. The idea is that when you push to github, there is a github action / webhook that is already that is looking for your pr and will go deploy its contents. Look at README.md and blueprints/README.md and blueprints/hello-world/*"
**AI Response**: Reviewed README.md, blueprints/README.md, hello-world, pipeline/README.md, codebuild.yml. Verdict: the Dockerfile is required (AgentCore runs container images; pipeline/README.md's "Adding a container image build" makes a Dockerfile step 1), but the local-build deploy script, private ECR repo, and deployed_by: manual were off-path. Rewired to pipeline-native: root Dockerfile with named target builder-mcp (codebuild.yml builds repo-root context), additive ArmContainerBuildProject (AgentCore needs arm64; reference x86 project untouched), Build stage exporting CONTAINER_DIGEST, BuilderMcpCloudFormation action deploying by digest, stacks.yml → deployed_by: pipeline. Deleted deploy.ps1 and builder-mcp/Dockerfile. Recorded DECISION-18 and GOTCHA-ARM/ROOT-DOCKERFILE/DEPLOY-ROLE.
**Context**: Operations — deployment method aligned with repo's intended path

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## Gates 1 & 2 Answered + Parallel Construction Directive
**Timestamp**: 2026-08-03T23:30:00Z
**User Input**: "Gate 1.1 - A, Gate 1.2 - A, Gate 1.3 - A, Gate  2.4 - A, Gate 2.5 - B, Gate 2.6 - C. Meaning??? Gate 2.7  - B.  Gate 2.8 - B. Gate 2.9 - C.  ----> Use  a small army of subagents to intelligently accomplish these tasks in parallel. Use smart spec-driven development style of managing many agents at once, using the build in ui tools to help us and the orchestrator agent (you) to keep track of what is getting made, and what is done. Schedule heartbeats every 15 minutes to keep things moving and do status checks.    One important edit: lets standardize the naming structure --> deployment_create, deployment_read, deployment_update, deployment_delete, and blueprint_search (and someday, blueprint_create, etc.)   A top priority subagent also should be researching STRANDS framework for AI MCP API writing, which was suggested as an alternative to fastapi, well optimized for working with genaI. I'm not familiar with it, so you should look into it, and then eventually have a subagent create a parallel implementation."
**AI Response**: All nine answers recorded in the gate files ([Answer]: tags filled) and the Extension Configuration table set to Yes/Yes/Yes. Gate 2.6 = C confirmed to mean "both formats" — Given/When/Then per story plus a demo-readiness checklist. Mob decision recorded: tool naming standardized to noun_verb (deployment_create/read/update/delete, blueprint_search; SPEC C3 contract change) — which also commissions the missing deployment_delete tool as a deregistration-PR flow. Six subagents launched in parallel: security compliance pass, resiliency assessment, property-based tests, User Stories Part 2, tool rename + deployment_delete, Strands framework research (top priority). Heartbeat scheduled every 15 minutes.
**Context**: Gates 1–2 closed; extensions enforced; parallel Construction under orchestration

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## Security Baseline Compliance Pass — Blocking Findings (extension requirement)
**Timestamp**: 2026-08-04T00:20:00Z
**Context**: Security Baseline enabled at Gate 1.1 (blocking constraints). Catch-up pass over
existing code returned **NON-COMPLIANT: 10 blocking, 9 advisory, 1 compliant, 4 N/A** — full
report in `construction/security-compliance.md`. Blocking findings (summary; per the
extension, these block stage completion until resolved):
1. F1 `propose_change`/`deployment_update` accepts arbitrary paths incl. `.github/workflows/*`,
   which execute on push before review — bypasses the review gate (server.py:189-226)
2. F2 shared credential, no object-level authorization; Cognito client secret retrievable via
   DescribeUserPoolClient
3. No logging anywhere in the package (SECURITY-03)
4. Unvalidated owner_netid / files / lengths (SECURITY-05)
5. Unhandled raise_for_status + orphaned-repo partial failures on execute paths (SECURITY-15)
6. Raw exception text leaked to callers (SECURITY-09)
7. No rate limiting / restart cap on a public endpoint (SECURITY-11)
8. No alarms, dashboards, or log retention (SECURITY-14)
9. Unpinned Docker base tag; no dependency scanning; no SBOM (SECURITY-10)
10. Undocumented wildcard-resource IAM statements incl. tag:GetResources on '*' (SECURITY-06)
**Status**: remediation task queued behind the in-flight tool-rename agent (same files).

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## Merge Milestone + Verify-and-Validate Dash
**Timestamp**: 2026-08-04T02:10:00Z
**User Input**: (abridged; verbatim stream in session transcript) Update stories.md: deprioritize dry_run to backlog; add a time limit to deploy retries (e.g. 30 min); Stage 7 Evolve is too much for MVP, Stage 8 stays. PR merged into main; team has AWS UI access via Jai (Tim's access pending; Jai is the team's merge rep). Identify which AWS services to watch to confirm the MCP deploys correctly. Skip Strands for now (backlog). Next key objective: verify and validate — after merge deploys, query the runtime with ~10 iterative calls per endpoint; start with one test deployment (hello-world); also draft the world's tiniest chatbot blueprint (canned responses, visible page) but hold deployment until hello-world verifies. Use subagents in parallel.
**AI Response**: Discovered PR #9 merged at daa7d85 — BEFORE the Entra swap and security remediation — so main is deploying the Cognito variant without the F1 gate-bypass fix. Merged origin/main back into builder and opened PR #11 (the two missing commits) with deploy-order notes for Jai. Launched four parallel agents: stories/backlog update, DEPLOYMENT-WATCH.md runbook, validate_endpoints.py harness (10 calls/tool, latency stats), tiny-chatbot blueprint (registered deployed_by: manual, parked).
**Context**: Operations — first real deployment in flight; verify-and-validate dash

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