Frank MCP Server
Provides tools for inspecting GitHub Actions workflow runs, failed jobs, job logs, and pull request check status, allowing agents to monitor CI/CD and determine mergeability.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Frank MCP ServerWhat's the status of the latest deployment?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Frank — the course MCP server
The teaching build for Claude for Engineering Teams — From Chat to Agent Pipelines, Sections 5–7. An MCP server that runs on AWS EC2 and gives every agent your team already uses — Claude Desktop, Claude Code, VS Code, GitHub Copilot — typed, audited, least-privilege tools over your infrastructure and GitHub pipeline.
One server. Every agent your team already uses.
This is a clean-room teaching build: small on purpose, every tool under ~40 lines, built live on camera in two passes.
The toolbox
Pass | Lecture | Tool | What it answers |
1 — infra | 5.3 |
| "How's the box?" |
1 — infra | 5.3 |
| "Is shipit up?" |
1 — infra | 5.3 |
| "What's it logging?" |
1 — infra | 5.3 |
| "What's deployed?" |
2 — pipeline | 5.4 |
| "Is CI green?" |
2 — pipeline | 5.4 |
| "What failed?" |
2 — pipeline | 5.4 |
| "Why did it fail?" |
2 — pipeline | 5.4 |
| "Can this PR merge?" |
Design rule (Lecture 5.3): each tool does one job with typed inputs and a small, capped output. Agents compose tools; we don't build "do everything" tools.
Related MCP server: KubeWhisper
Security posture (Lecture 5.5)
Credential boundary: Frank holds the IAM role and the GitHub PAT. Laptops and prompts never see a secret.
Fine-grained PAT: one repo, Actions: read. Frank observes; the repair agent writes with its own credential.
IAM: read-mostly, region-pinned, no wildcards (
deploy/iam-policy.json).Transport: bearer-token auth, private bind, tunnel/VPN access only.
Allowlists everywhere: services Frank may inspect are enumerated in config, not discovered.
Audit: every tool call is a loggable event; systemd hardening in
deploy/frank.service.
Quick start (local, no AWS needed)
python3 -m venv .venv && .venv/bin/pip install -r requirements.txt
export FRANK_AUTH_TOKEN=$(python -c "import secrets; print(secrets.token_urlsafe(32))")
.venv/bin/python -m frank.server
# then: claude mcp add --transport http frank http://127.0.0.1:8720/mcp \
# --header "Authorization: Bearer $FRANK_AUTH_TOKEN"instance_health, service_status, and tail_log read /proc and systemd,
so they return real data on any Linux box. GitHub tools need
FRANK_GITHUB_TOKEN + FRANK_GITHUB_REPO (see .env.example).
EC2 deployment, IAM, and client wiring: deploy/ec2-setup.md.
Repo layout
frank/
config.py # all configuration, all from env
tools_infra.py # pass 1 — Lecture 5.3
tools_github.py # pass 2 — Lecture 5.4
server.py # FastMCP wiring + auth — Lectures 5.5–5.6
deploy/
frank.service # systemd unit, hardened
iam-policy.json # read-mostly instance role
ec2-setup.md # the on-camera deployment walkthroughRecording checkpoints
Tag the repo as you record so students can check out each lecture's state:
git tag lecture-5.3 after pass 1, lecture-5.4 after pass 2,
lecture-5.5 after auth + hardening.
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