page:recipes:mcp server:flask:worker state

Host mcp server with Flask: worker execution and job state

Deploy a mcp server built with Flask 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 Flask: 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). Not separately tested: your job payloads, retry policy and scheduling; treat the mcp server-specific behavior as your application code.

Representative Queries

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

Resource Requirements

• primitive:compute
• primitive:postgres

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.

Framework

• Flask

Workload

• MCP server

Release Status

• Published

Support Status

• Verified

Execution Status

• Ready

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.
• Both services read DATABASE_URL at runtime and share one jobs table.
• An Ample account token with servers:write and databases:write.

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.
   • Command: ample plan --write .
2. Share one database: Keep a single [databases.main] with engine = "postgres", drop any per-service database the planner added.
   • Command: ample plan --offline .
3. Apply: Reconcile the whole manifest in dependency order: the database first, then both services.
   • Command: ample up .
4. Verify: Fetch the web service URL and its worker status route and confirm the worker processed the enqueued job.
   • Command: ample logs --kind runtime

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 app.py

Cost Estimate

• Currency: USD
• Monthly Amount: 15.0
• Components:
  • Web server: monthly amount 5.0
  • Worker server: monthly amount 5.0
  • Managed PostgreSQL database: monthly amount 5.0

Limitations

• Verified on the python-3.12 template at s-1vcpu-1gb for both services with the example fixture; other sizes, templates, and Flask major versions are not 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.

Success Checks

• Web service responds on its public URL.
• Worker consumed the enqueued job.

Evidence Summary

• Flask web service plus a separate Python worker process deployed on Ample. The web service enqueued a job that the private worker service consumed from the shared managed PostgreSQL database.