agentrq-bridge · v0.1.0 · 2026-09-01 · sha256 d6bb32085b74866c
agentrq-bridge v0.1.0A
Immutable. This exact content never changes and is served at /api/v1/blob/d6bb32085b74866c.
---
name: agentrq-bridge
description: "AgentRQ integration: structured HITL task board, permission gating, and real-time workspace bridge via MCP Streamable HTTP"
version: 0.1.0
type: extension
runtime: python3
entry: plugin.py
plugin_api: "2.0"
permissions:
- net
- tool
- route
- widget
- read_settings
- companion_process
- inject_chat
env_from_settings:
- AGENTRQ_MCP_URL
- AGENTRQ_TOKEN
when_to_use: >
User wants to interact with an AgentRQ workspace: pull tasks, create tasks
for human review, reply to task threads, update task status, or request
human permission for sensitive actions.
companion_processes:
- name: agentrq_listener
command: [python3, listener.py]
runtime: python3
timeout_sec: 120
ui_tab:
tab_id: dashboard
title: AgentRQ
icon: tasks
render:
kind: declarative
schema_version: 1
components:
- type: poll
route: status
method: GET
interval_sec: 15
components:
- type: kv
fields:
- label: Connected
path: connected
- label: Workspace
path: name
- label: Description
path: description
- label: Agent Online
path: agent_connected
---
# AgentRQ Bridge
Connects Ouroboros to an [AgentRQ](https://github.com/agentrq/agentrq)
workspace via the MCP Streamable HTTP transport. AgentRQ is a task
orchestration platform for structured human-agent collaboration.
## What it provides
- **6 agent tools** that map to the AgentRQ per-workspace MCP surface:
`rq_workspace`, `rq_pull_next`, `rq_create_task`, `rq_reply`,
`rq_update_status`, `rq_get_messages`.
- **Real-time SSE listener** — a companion process that holds a
persistent SSE connection to the AgentRQ MCP endpoint and
injects events (new tasks, human replies, permission verdicts)
into Ouroboros chat in real time via the Host Service API.
- **Declarative widget** showing live workspace connection status.
- **Zero external dependencies** — uses only Python stdlib (`urllib`,
`json`, `socket`, `signal`).
## Setup
1. Deploy AgentRQ (Docker: `docker pull agentrq/agentrq:latest` or
self-host via [SETUP.md](https://github.com/agentrq/agentrq/blob/main/SETUP.md)).
2. Create a workspace in the AgentRQ UI. Copy its **MCP URL** and **Token**
from the workspace setup modal.
3. In Ouroboros **Settings → Secrets**, add two keys:
- `AGENTRQ_MCP_URL` — the workspace MCP endpoint
(e.g. `https://WORKSPACE_ID.mcp.agentrq.com/` or
`http://localhost:8080/mcp/WORKSPACE_ID`)
- `AGENTRQ_TOKEN` — the 16-char workspace token
4. Enable this skill and grant the two keys when prompted.
## Agent workflow
```
rq_workspace() → see mission + stats
rq_pull_next() → dequeue next task
rq_update_status(ongoing) → mark task in progress
... do the work ...
rq_reply(task_id, result) → post result to task thread
rq_update_status(completed)→ mark task done
```
To request human permission for a sensitive action:
```
rq_create_task(title="Approve: deploy to prod", assignee="human")
→ human sees it in AgentRQ UI, replies allow/deny
rq_get_messages(task_id) → read the verdict
```