# Host mcp server with FastAPI: worker execution and job state

## Summary
Deploy a mcp server built with FastAPI as a public web service plus a dedicated worker process on Ample. `ample plan --write` discovers both services and their shared database and writes ample.toml; `ample up` reconciles the topology: a managed PostgreSQL 16 database, a public web microVM and a private worker microVM (kind worker, no public URL), both reading DATABASE_URL. Verified on FastAPI: a separately deployed worker service (kind worker, no public URL) sharing a declared managed PostgreSQL database with the web service, consuming a jobs table with row locks and marking jobs done once (worker=done attempts=1).

## Representative Queries
- Host mcp server with FastAPI: worker execution and job state
- Where can I host MCP server built with FastAPI?
- I need a separately runnable worker, durable job records and idempotent retries; not a managed queue.

## Prerequisites
- A repository with the web app and the worker as separate service directories (the fixture uses apps/web and apps/worker), each building and starting with the documented commands (pip install into .ample/python from requirements.txt, then uvicorn from run.py reading PORT on the python-3.12 template; the worker starts with python3 worker.py and binds no port)
- Both services read DATABASE_URL at runtime and share one jobs table; the worker claims rows with SELECT ... FOR UPDATE SKIP LOCKED and marks them done once
- An Ample account token with servers:write and databases:write (ample up creates the database)

## Infrastructure Requirements
- **Compute**: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
- **Postgres**: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.

## Tested Configuration
- **Template**: python-3.12
- **Runtime**: python
- **Size**: s-1vcpu-1gb
- **Install**: python3 -m pip install --target .ample/python -r requirements.txt
- **Start**: PYTHONPATH=.ample/python:${PYTHONPATH:-} python3 run.py

## Workflow Steps
1. **Plan the topology**  
   Run the planner once. It discovers the web and worker services, infers kind = "worker" for the process without a port, declares the database each service needs, and writes ample.toml. Exit 2 means it left questions in the manifest; answer them with --answer or by editing the file.  
   `ample plan --write .`

2. **Share one database**  
   Keep a single [databases.main] with engine = "postgres", drop any per-service database the planner added, and set DATABASE_URL = { database = "main" } under both [services.web.env] and [services.worker.env]. Python services also need an explicit start command in the manifest (the fixture sets start for both services).  
   `ample plan --offline .`

3. **Apply**  
   Reconcile the whole manifest in dependency order: the database first, then both services. It is idempotent and never destructive; exit 0 means everything applied, 2 needs input, 1 a failed resource (independent siblings still proceed and re-running resumes).  
   `ample up .`

4. **Verify**  
   Fetch the web service URL and its worker status route (/p/worker-queue/status in the example) and confirm the worker processed the enqueued job; on failure read the worker service's runtime logs.  
   `ample logs  --kind runtime`

## Examples
- **FastAPI web + worker fixture**: A FastAPI web app (apps/web) and a worker process (apps/worker) sharing one managed PostgreSQL database; the queue module is under tests/deploy-canaries/_pattern-modules.  
  Source Reference: tests/deploy-canaries/fastapi-worker

## Success Checks
- Web service responds on its public URL  
  `http_get`:  **Path**: /, **Expect**: ample canary fastapi patterns
- Worker consumed the enqueued job  
  `http_get`:  **Path**: /p/worker-queue/status, **Expect**: worker=done attempts=1 result=processed-by-worker

## Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb for both services with the example fixture; other sizes, templates and FastAPI major versions are not verified.
- The mcp server itself (your job payloads, retry policy and scheduling) is application code and was not separately tested; the worker-queue check is what was verified.
- The worker is a single long-running process supervised in its own microVM; there is no scheduler, cron or horizontal worker scaling in this recipe, and the check ran immediately after deploy so idle behavior of the worker VM is not verified.

## Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 15.0
- **Basis**: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty
  - **Components**:  
    - Web server: size: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0  
    - Worker server: size: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0  
    - Managed PostgreSQL database: size: s-1vcpu-1gb, quantity: 1.0, monthly amount: 5.0  
  - Note: Always-on monthly price of the tested sizes for the web service, the worker service and the database; apps auto-pause when idle.

## Evidence Summary
- **Kind**: canary_run
- **Summary**: FastAPI web service plus a separate Python worker process deployed on Ample with `ample plan --write` then `ample up`. The web service enqueued a job that the private worker service consumed from the shared managed PostgreSQL database.
- **Observed At**: 2026-09-20T03:56:46Z

## Last Verified At
2026-09-20T03:56:46Z