Stromy Workflows MCP

Hosted workflow discovery, validation, execution, and lifecycle facade for Stromy

Built with FastMCP 3.0 and managed with uv.

The facade is deliberately thin and client-agnostic: verified Entra app roles scope every run; Stromy owns the Postgres schema and execution worker; this service performs DML only, validates tiered contracts, and starts ACA Job executions with server-controlled templates.

Tools

• list_workflows / describe_workflow / validate_config

• start_run / run_status / list_runs

• resume_run / cancel_run / get_results

• fs_list / fs_read for the hosted wf-* skills

Tier 1 keys are interview questions, tier 2 keys are caller-overridable defaults, and tier 3 keys are provider-locked. Client tokens cannot see or set tier 3. Run ownership comes only from verified client.<slug> roles; a chat-supplied slug can narrow scope but never grant it.

Related MCP server: Procesio MCP Server

Setup

uv sync
cp .env.example .env

Run

# stdio (default)
uv run python -m stromy_workflows_mcp.server

# Or via the FastMCP CLI (reads fastmcp.json):
uv run fastmcp run
uv run fastmcp dev      # with the Inspector UI

HTTP transport is enabled by default — the server listens on http://127.0.0.1:8000/mcp/.

Project layout

src/stromy_workflows_mcp/server.py        FastMCP server entrypoint (instance: `mcp`)
src/stromy_workflows_mcp/config.py        Settings via pydantic-settings (reads .env)
components/
├── tools/                 @tool functions, auto-discovered
├── resources/             @resource functions, auto-discovered
└── prompts/               @prompt functions, auto-discovered
skills/
└── server-guide/          Skill served via the fs_read/fs_list tools
components/resources/contracts/  Generated from Stromy's authored contracts
tests/                     pytest + in-memory FastMCP Client

Components are loaded by FileSystemProvider. Drop a new .py file into any subdirectory of components/ with a standalone @tool / @resource / @prompt decorator — no registration required. Set MCP_DEV_MODE=true in .env to enable hot-reload during development.

Skills

The skills/ directory is served through the generic fs_read / fs_list tools rather than MCP resources, so skills reach every client (the Claude app, ChatGPT, etc.) — not only clients that surface resources. Discover skills with fs_list("skills") and load one with fs_read("skills/<name>/SKILL.md"). The tools are jailed to the configured fs_roots (default ["skills"]); paths that escape via .., absolute paths, or symlinks are rejected.

Drop a new folder into skills/ with a SKILL.md — no registration needed.

Tests

uv run pytest
uv run ruff check
uv run pyright
python3 scripts/sync_contracts.py --source-root ../../Stromy --check

GET /health is a readiness check, not a cosmetic liveness response. It returns 503 when Postgres is unreachable or schema_meta.version is outside the facade's supported range. Deploy order is therefore Stromy migration first, facade second.

Use with Claude Code

The included .mcp.json registers this server as stromy-workflows-mcp for any Claude Code session opened in this directory.

OAuth (Microsoft Entra ID)

This server supports optional OAuth authentication via Microsoft Entra ID. When enabled, HTTP/SSE clients must authenticate via browser-based Azure login before accessing MCP tools. Stdio transport is unaffected.

Azure App Registration

1. Go to Azure Portal → App registrations → New registration

2. Name: stromy-workflows-mcp-oauth

3. Supported account types: Single tenant (Accounts in this organizational directory only)

4. Redirect URI: Web → http://localhost:8000/auth/callback (update for production)

5. After creation, go to Authentication and ensure Access tokens and ID tokens are checked under "Implicit grant and hybrid flows"

Token version

Go to Manifest and set "accessTokenAcceptedVersion": 2 (required by FastMCP's AzureProvider).

Expose an API

1. Go to Expose an API → Set Application ID URI (accept default api://<client-id>)

2. Add a scope: mcp.access — "Access MCP server" — Admins and users

Client secret

1. Go to Certificates & secrets → New client secret

2. Copy the Value (not the Secret ID) — this is OAUTH_CLIENT_SECRET

Configuration

Fill in .env:

OAUTH_ENABLE=true
OAUTH_CLIENT_ID=<Application (client) ID from Overview>
OAUTH_CLIENT_SECRET=<Client secret Value>
OAUTH_TENANT_ID=<Directory (tenant) ID from Overview>
OAUTH_BASE_URL=http://localhost:8000
OAUTH_REQUIRED_SCOPES=mcp.access

Production deployment on Azure Container Apps

Store secrets separately from plain env vars:

APP=stromy-workflows-mcp
RG=rg-stromy-workflows-mcp

az containerapp secret set --name $APP --resource-group $RG \
  --secrets oauth-client-secret="<your-secret>"

az containerapp update --name $APP --resource-group $RG \
  --set-env-vars \
    OAUTH_ENABLE=true \
    OAUTH_CLIENT_ID=<client-id> \
    OAUTH_TENANT_ID=<tenant-id> \
    OAUTH_BASE_URL=https://<your-app-fqdn> \
    OAUTH_REQUIRED_SCOPES=mcp.access \
    OAUTH_CLIENT_SECRET=secretref:oauth-client-secret

Durable sessions

FastMCP keeps OAuth state — the JWT signing key, dynamically-registered clients, and upstream tokens. The keys it needs (signing key, storage encryption key, storage path) are derived deterministically from the stable OAuth client secret, so they already survive restarts with no configuration. The only ephemeral piece is the store directory contents on the container's local disk, which Azure Container Apps wipes on every cold start / scale-to-zero — invalidating the tokens clients hold and forcing them to re-authenticate.

The fix is infrastructure, not app code: a persistent Azure Files share mounted at FastMCP's home path (/home/appuser/.local/share/fastmcp) makes the store dir survive restarts. No Redis, no extra dependencies, no extra env vars, no extra secrets (ORG-PLAN-073).

On Azure this is provisioned automatically when the server is registered with enable_oauth = true — the generated terraform fragment carries "oauth_sessions": "files", which mounts the share. BENIGN under the cost policy (a per-use file share). Nothing to configure by hand.

Locally, the default on-disk / in-memory store needs no configuration, so uv run pytest and fastmcp run work out of the box.

Deploy to Azure Container Apps

Production runs on Azure Container Apps with scale-to-zero. CI/CD is handled by .github/workflows/deploy-aca.yml on every push to main.

See azure_aca/README.md for the full setup guide (automated script or manual commands).