robo-cortex
mcpopen · packageio.github.robotel-limited/robo-cortex · v0.4.1
Git-aware memory store for AI coding agents; memories are anchored to git blob hashes.
run it
on your own machines, one way per deploy methodgenerated from the record, not tested yet
#!/usr/bin/env bash # robo-cortex (io.github.robotel-limited/robo-cortex), recipe baremetal (generated). # Generated by Hub for toolset "my-agent"; started by mcp-my-agent-robo-cortex.service. set -euo pipefail export HOST=127.0.0.1 PORT=8101 exec uvx mcp-proxy --host 127.0.0.1 --port 8101 --pass-environment -- uvx robo-cortex==0.4.1 [Unit] Description=MCP server robo-cortex (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/robo-cortex WorkingDirectory=/var/lib/mcp/robo-cortex ExecStart=/opt/mcp/my-agent/bin/robo-cortex.sh Restart=on-failure RestartSec=5 NoNewPrivileges=true ProtectSystem=strict ProtectHome=true PrivateTmp=true ReadWritePaths=/var/lib/mcp/robo-cortex [Install] WantedBy=multi-user.target
generated from the record, not tested yet
docker run --rm -p 127.0.0.1:8101:8000 ghcr.io/astral-sh/uv:python3.12-bookworm-slim sh -c 'uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx robo-cortex==0.4.1'
generated from the record, not tested yet
# Generated by Hub for toolset "my-agent" (2026-10-18T00:31:36+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:
robo-cortex:
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 robo-cortex==0.4.1
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
volumes:
npm-cache: {}
uv-cache: {}
generated from the record, not tested yet
# Generated by Hub for toolset "my-agent" (2026-10-18T00:31:36+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: robo-cortex
namespace: mcp
labels: &id001
app: robo-cortex
spec:
replicas: 1
selector:
matchLabels: *id001
template:
metadata:
labels: *id001
spec:
containers:
- name: robo-cortex
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
ports:
- containerPort: 8000
name: http
env: []
command:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx robo-cortex==0.4.1
readinessProbe:
httpGet:
path: /status
port: http
initialDelaySeconds: 10
---
apiVersion: v1
kind: Service
metadata:
name: robo-cortex
namespace: mcp
spec:
selector:
app: robo-cortex
ports:
- port: 8000
targetPort: http
name: http
generated from the record, not tested yet
# Generated by Hub for toolset "my-agent" (2026-10-18T00:31:36+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:
robo-cortex:
enabled: true
replicas: 1
port: 8000
path: /mcp
container:
name: robo-cortex
image: ghcr.io/astral-sh/uv:python3.12-bookworm-slim
ports:
- containerPort: 8000
name: http
env: []
command:
- sh
- -c
- uvx mcp-proxy --host 0.0.0.0 --port 8000 --pass-environment -- uvx robo-cortex==0.4.1
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
-
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 deployment's outputs list the endpoints.
connect to it
copy what your client needsuvx robo-cortex==0.4.1
{
"mcpServers": {
"robo-cortex": {
"command": "uvx",
"args": [
"robo-cortex==0.4.1"
]
}
}
}
#!/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 robo-cortex -- uvx robo-cortex==0.4.1
{
"mcpServers": {
"robo-cortex": {
"command": "uvx",
"args": [
"robo-cortex==0.4.1"
]
}
}
}
{
"servers": {
"robo-cortex": {
"type": "stdio",
"command": "uvx",
"args": [
"robo-cortex==0.4.1"
]
}
}
}
name: my-agent target: local servers: - hub: io.github.robotel-limited/robo-cortex
- not probed yet: tools unpinned, ingest lists them
tools
Probe result: faileddocker: the container exited: ^ | File "<path>", line 306, in send_request | raise McpError(response_or_error.error) | mcp.shared.exceptions.McpError: Connection closed +------------------------------------; baremetal: MCPError: Connection closed; server stderr: …Attach or verify evidence link Link two memories as contradicting or duplicate mcp Run the MCP server (stdio) export Export memories to JSONL import Import memories from JSONL merge Merge two JSONL knowledge bases hooks Manage robo-cor…
runs · 1
the latest tests of this entry by the hub and its workers, newest first| date | worker | method | status | sandbox | reason |
|---|---|---|---|---|---|
| 2026-10-17 08:40 | local-mac-vm | docker | failed | gvisor | docker: the container exited: ^ | File "<path>", line 306, in send_request | raise McpError(response_or_error.error) | mcp.shared.exceptions.McpError: Connectio… |