Real-Time Rail Predictions
apiauth · remotecom.wmata/rail-realtime · v1.0
Real-time rail prediction methods.
run it
on your own machines, one way per deploy methodgenerated from the record, not tested yet
An OpenAPI-to-MCP bridge, for clients without callbus in front.
# once, as root:
# as_mcp DIR COMMAND...: runs COMMAND as the mcp user in DIR, its home, sandboxed as the
# units are: a package's install scripts can write to DIR only, as the server later can
as_mcp() {
local dir="$1"; shift
systemd-run --quiet --wait --pipe --collect --uid=mcp --gid=mcp \
-p WorkingDirectory="$dir" -p Environment=HOME="$dir" -p ReadWritePaths="$dir" \
-p NoNewPrivileges=true -p ProtectSystem=strict -p ProtectHome=true -p PrivateTmp=true \
-- "$@" </dev/null
}
install -d -m 0750 -o mcp -g mcp /var/lib/mcp/rail-realtime
# rail-realtime: its packages, installed whole before its unit starts (no session installs)
systemctl stop mcp-my-agent-rail-realtime.service 2>/dev/null || true
as_mcp /var/lib/mcp/rail-realtime uv tool install awslabs.openapi-mcp-server
as_mcp /var/lib/mcp/rail-realtime uv tool install mcp-proxy
#!/usr/bin/env bash
# rail-realtime (com.wmata/rail-realtime), recipe baremetal (generated).
# Generated by Hub for toolset "my-agent"; started by mcp-my-agent-rail-realtime.service.
set -euo pipefail
export HOST=127.0.0.1 PORT=8101
export API_NAME=rail-realtime
export API_SPEC_URL=https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json
export API_BASE_URL=https://api.wmata.com/StationPrediction.svc
export AUTH_TYPE=api_key
export "AUTH_API_KEY=${RAIL_REALTIME_API_KEY}"
export AUTH_API_KEY_NAME=api_key
export AUTH_API_KEY_IN=header
exec uvx mcp-proxy --host 127.0.0.1 --port 8101 --pass-environment -- uvx awslabs.openapi-mcp-server
[Unit]
Description=MCP server rail-realtime (toolset my-agent), generated by Hub
After=network-online.target
Wants=network-online.target
[Service]
Type=simple
User=mcp
Group=mcp
EnvironmentFile=/etc/mcp/my-agent.env
Environment=HOME=/var/lib/mcp/rail-realtime
WorkingDirectory=/var/lib/mcp/rail-realtime
ExecStart=/opt/mcp/my-agent/bin/rail-realtime.sh
Restart=on-failure
RestartSec=5
NoNewPrivileges=true
ProtectSystem=strict
ProtectHome=true
PrivateTmp=true
ReadWritePaths=/var/lib/mcp/rail-realtime
[Install]
WantedBy=multi-user.target
generated from the record, not tested yet
An OpenAPI-to-MCP bridge, for clients without callbus in front.
docker run --rm -p 127.0.0.1:8101:8000 -e API_NAME -e API_SPEC_URL -e API_BASE_URL -e AUTH_TYPE -e AUTH_API_KEY -e AUTH_API_KEY_NAME -e AUTH_API_KEY_IN ghcr.io/astral-sh/uv:python3.12-bookworm-slim sh -c 'uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx awslabs.openapi-mcp-server'
generated from the record, not tested yet
An OpenAPI-to-MCP bridge, for clients without callbus in front.
# Generated by Hub for toolset "my-agent" (2026-10-18T17:47:32+00:00).
# Each package server runs behind a stdio->HTTP bridge and listens on localhost only.
# cp .env.example .env # fill the ${VAR}s
# docker compose up -d && bash smoke.sh
# Remote servers are not here: clients reach them directly (see clients/).
name: mcp-my-agent
services:
rail-realtime:
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
command:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx awslabs.openapi-mcp-server
ports:
- 127.0.0.1:8101:8000
volumes:
- uv-cache:/root/.cache/uv
healthcheck:
test:
- CMD
- python3
- -c
- import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/status')
interval: 30s
timeout: 5s
retries: 5
start_period: 2m
restart: unless-stopped
x-note: An OpenAPI-to-MCP bridge, for clients without callbus in front.
environment:
API_NAME: rail-realtime
API_SPEC_URL: https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json
API_BASE_URL: https://api.wmata.com/StationPrediction.svc
AUTH_TYPE: api_key
AUTH_API_KEY: ${RAIL_REALTIME_API_KEY}
AUTH_API_KEY_NAME: api_key
AUTH_API_KEY_IN: header
volumes:
npm-cache: {}
uv-cache: {}
generated from the record, not tested yet
An OpenAPI-to-MCP bridge, for clients without callbus in front.
# Generated by Hub for toolset "my-agent" (2026-10-18T17:47:32+00:00).
# kubectl create namespace mcp
# kubectl -n mcp create secret generic mcp-credentials --from-env-file=.env
# kubectl apply -f kubernetes.yaml
# Services are cluster-internal: <name>.mcp.svc.cluster.local:8000/mcp. Put an ingress
# with auth in front before exposing any of them.
apiVersion: v1
kind: Namespace
metadata:
name: mcp
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: rail-realtime
namespace: mcp
labels: &id001
app: rail-realtime
spec:
replicas: 1
selector:
matchLabels: *id001
template:
metadata:
labels: *id001
spec:
containers:
- name: rail-realtime
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
ports:
- containerPort: 8000
name: http
env:
- name: API_NAME
value: rail-realtime
- name: API_SPEC_URL
value: https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json
- name: API_BASE_URL
value: https://api.wmata.com/StationPrediction.svc
- name: AUTH_TYPE
value: api_key
- name: AUTH_API_KEY
valueFrom:
secretKeyRef:
name: mcp-credentials
key: RAIL_REALTIME_API_KEY
- name: AUTH_API_KEY_NAME
value: api_key
- name: AUTH_API_KEY_IN
value: header
args:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx awslabs.openapi-mcp-server
readinessProbe:
httpGet:
path: /status
port: http
initialDelaySeconds: 10
---
apiVersion: v1
kind: Service
metadata:
name: rail-realtime
namespace: mcp
spec:
selector:
app: rail-realtime
ports:
- port: 8000
targetPort: http
name: http
generated from the record, not tested yet
An OpenAPI-to-MCP bridge, for clients without callbus in front.
# Generated by Hub for toolset "my-agent" (2026-10-18T17:47:32+00:00).
# Credentials come from the Secret 'mcp-credentials' (kubectl create secret generic ... --from-env-file=.env).
# Each server under `servers` is one Deployment + Service; the keys after it configure
# upstream charts a worker verified.
servers:
rail-realtime:
enabled: true
replicas: 1
port: 8000
path: /mcp
container:
name: rail-realtime
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
ports:
- containerPort: 8000
name: http
env:
- name: API_NAME
value: rail-realtime
- name: API_SPEC_URL
value: https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json
- name: API_BASE_URL
value: https://api.wmata.com/StationPrediction.svc
- name: AUTH_TYPE
value: api_key
- name: AUTH_API_KEY
valueFrom:
secretKeyRef:
name: mcp-credentials
key: RAIL_REALTIME_API_KEY
- name: AUTH_API_KEY_NAME
value: api_key
- name: AUTH_API_KEY_IN
value: header
args:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx awslabs.openapi-mcp-server
readinessProbe:
httpGet:
path: /status
port: http
initialDelaySeconds: 10
# helm install my-agent helm/my-agent -n mcp
in the cloud
one click: the provider's deploy form opens filled in, in your own account- koyeb
-
The form opens with CHANGE_ME for each value you supply: RAIL_REALTIME_API_KEY. Fill them in before you deploy.
Clients connect to the service's https://…koyeb.app address plus /mcp.
- azure
-
A Container Apps environment with one app per server, each with HTTPS ingress and one replica. The portal asks for each value you supply as a secure parameter; the deployment's outputs list the endpoints.
connect to it
copy what your client needsuvx awslabs.openapi-mcp-server
{
"mcpServers": {
"rail-realtime": {
"command": "uvx",
"args": [
"awslabs.openapi-mcp-server"
],
"env": {
"API_NAME": "rail-realtime",
"API_SPEC_URL": "https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json",
"API_BASE_URL": "https://api.wmata.com/StationPrediction.svc",
"AUTH_TYPE": "api_key",
"AUTH_API_KEY": "${RAIL_REALTIME_API_KEY}",
"AUTH_API_KEY_NAME": "api_key",
"AUTH_API_KEY_IN": "header"
}
}
}
}
#!/usr/bin/env bash
# Registers every server with Claude Code (run once; `claude mcp list` to check).
set -euo pipefail
set -a; [ -f .env ] && source .env; set +a
claude mcp add rail-realtime -e API_NAME=rail-realtime -e API_SPEC_URL=https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json -e API_BASE_URL=https://api.wmata.com/StationPrediction.svc -e AUTH_TYPE=api_key -e "AUTH_API_KEY=${RAIL_REALTIME_API_KEY}" -e AUTH_API_KEY_NAME=api_key -e AUTH_API_KEY_IN=header -- uvx awslabs.openapi-mcp-server
{
"mcpServers": {
"rail-realtime": {
"command": "uvx",
"args": [
"awslabs.openapi-mcp-server"
],
"env": {
"API_NAME": "rail-realtime",
"API_SPEC_URL": "https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json",
"API_BASE_URL": "https://api.wmata.com/StationPrediction.svc",
"AUTH_TYPE": "api_key",
"AUTH_API_KEY": "${RAIL_REALTIME_API_KEY}",
"AUTH_API_KEY_NAME": "api_key",
"AUTH_API_KEY_IN": "header"
}
}
}
}
{
"servers": {
"rail-realtime": {
"type": "stdio",
"command": "uvx",
"args": [
"awslabs.openapi-mcp-server"
],
"env": {
"API_NAME": "rail-realtime",
"API_SPEC_URL": "https://api.apis.guru/v2/specs/wmata.com/rail-realtime/1.0/swagger.json",
"API_BASE_URL": "https://api.wmata.com/StationPrediction.svc",
"AUTH_TYPE": "api_key",
"AUTH_API_KEY": "${RAIL_REALTIME_API_KEY}",
"AUTH_API_KEY_NAME": "api_key",
"AUTH_API_KEY_IN": "header"
}
}
}
}
name: my-agent target: local servers: - hub: com.wmata/rail-realtime
- not probed yet: tools unpinned, ingest lists them
- the API key goes in the query (api_key): callbus sends headers only, use the OpenAPI bridge (callbus: false)
operations
Probe result: failedremote: Swagger 2.0: the hub's entry needs an OpenAPI 3 spec
runs · 2
the latest tests of this entry by the hub and its workers, newest first| date | worker | method | status | sandbox | reason |
|---|---|---|---|---|---|
| 2026-10-17 09:41 | local-mac | remote | failed | none | remote: Swagger 2.0: the hub's entry needs an OpenAPI 3 spec |
| 2026-10-16 09:39 | local-mac | remote | failed | none | remote: Swagger 2.0: the hub's entry needs an OpenAPI 3 spec |