Host MCP Server with Flask: Stored Input and Output Artifacts

Summary

Deploy a mcp server built with Flask on Ample using the generated downloads pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, a private S3-compatible bucket holds objects with credentials delivered as encrypted environment variables. Verified on Flask: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). Not separately tested: your export formats, retention policy and entitlement model; treat the mcp server-specific behavior as your application code.

Representative Queries

• Host mcp server with Flask: stored input and output artifacts
• Where can I host MCP server built with Flask?
• I need an input/output artifact contract, object metadata and access boundaries.

Resource Requirements

• primitive:compute
• primitive:postgres
• primitive:s3-compatible-object-storage

Infrastructure Requirements

1. Compute

   • Status: verified
   • Summary: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
   • More Info: Compute

2. Postgres

   • Status: verified
   • Summary: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.
   • More Info: Postgres

3. S3-compatible object storage

   • Status: verified
   • Summary: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.
   • More Info: S3

Prerequisites

• A Flask project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template)
• A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
• A bucket from ample bucket create with its credentials passed as encrypted S3_* environment variables
• An Ample account token with servers:write, databases:read, buckets:read

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

Workflow Steps

1. Build and start
   pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.

2. Implement the pattern on PostgreSQL
   The fixture's module implements generated downloads: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.

3. Wire object storage
   Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing. Keep private data in an unpublished bucket.

4. Deploy
   Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked). Re-running with no change is a no-op.

   ample deploy . --name <name> --public --start "python3 app.py" --env S3_ENDPOINT=<endpoint> --env S3_REGION=<region> --env S3_BUCKET=<bucket> --env S3_ACCESS_KEY_ID=<access_key> --env S3_SECRET_ACCESS_KEY=<secret_key>  
   

5. Verify
   Fetch the live URL and the pattern self-test route(s) (/p/generated-downloads) from the example; then run your own checks. On failure read ample logs --kind build then --kind runtime.

   ample logs  --kind build  
   

Success Checks

1. App Responds

   • Kind: http_get
   • Path: /
   • Expect: ample canary flask patterns

2. Generated Downloads Self-test

   • Kind: http_get
   • Path: /p/generated-downloads
   • Expect: export=ok rows=3 (with ?token=...; 401 without)

Limitations

• Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Flask major versions are not verified.
• The mcp server itself (your export formats, retention policy and entitlement model) is application code and was not separately tested; the pattern checks are what was verified.

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Basis: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty

Cost Components

1. App server

   • Size: s-1vcpu-1gb
   • Quantity: 1.0
   • Monthly Amount: 5.0

2. Managed PostgreSQL database

   • Size: s-1vcpu-1gb
   • Quantity: 1.0
   • Monthly Amount: 5.0

Additional Note

Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.

Evidence Summary

• Canary Run: Flask pattern fixture deployed on Ample (pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template); checks passed for generated-downloads and configuration-secrets. Pattern proof: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3).

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