agenthub-monitor
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agenthub-monitorshow the current pipeline dashboard"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AgentHub Monitor
An MCP App server: it renders an interactive pipeline dashboard inside the host window (Claude Desktop, Claude Code, and other MCP App–capable clients) instead of returning a wall of text.
The dashboard shows two things side by side:
DAG state — nodes of a pipeline run, grouped into waves, each with its own status.
Harness metrics — scenario pass rate, critical failures, accumulated cost and latency.
Point it at your own pipeline's JSON export and it becomes a live view of your runs. With no configuration it serves a built-in sample, so the UI is useful the moment you install it.
Tools
Tool | What it does | Read-only |
| Renders the dashboard inline in the host | yes |
| Returns the current pipeline state as structured JSON | yes |
| Records an action request in the server's own state | no |
trigger_action does not execute anything. It annotates the server's in-memory state so the
dashboard can show that an action was requested. This server runs no commands, spawns no
processes, and makes no network calls.
Related MCP server: mcp-a2ui-vega
Install
Requires Python 3.10+. No third-party dependencies.
git clone https://github.com/NEVELSK65/mcp-agenthub-monitor.git
cd mcp-agenthub-monitor
python3 -m unittest discover -s tests # optional: verifyConfigure
Add to your MCP client configuration:
{
"mcpServers": {
"agenthub-monitor": {
"command": "python3",
"args": ["/absolute/path/to/mcp-agenthub-monitor/server.py"],
"env": {
"AGENTHUB_STATE_FILE": "/absolute/path/to/your/pipeline-state.json"
}
}
}
}AGENTHUB_STATE_FILE is optional. Without it the server returns sample data, flagged with
is_sample_data: true so it is never mistaken for a real run.
State file format
Write this JSON from your own CI, orchestrator, or test harness:
{
"dag": {
"title": "Nightly build",
"total_nodes": 6,
"completed_nodes": 4,
"waves": 3,
"node_states": {
"node_01_checkout": "COMPLETED",
"node_02_unit_tests": "COMPLETED",
"node_03_integration": "RUNNING",
"node_04_security_scan": "PENDING"
}
},
"harness": {
"pass_rate_pct": 93.75,
"total_scenarios": 16,
"passed_scenarios": 15,
"critical_failures": 0,
"total_cost_usd": 0.112,
"total_latency_ms": 41700
},
"log": "Integration stage in progress."
}The file is re-read on every tool call, so the dashboard reflects whatever your pipeline last wrote.
Node status strings are passed through to the UI as-is; COMPLETED, RUNNING, PENDING and
FAILED get distinct colours.
Resource
The UI is exposed as an MCP resource at ui://agenthub/mcp-app.html with MIME type
text/html;profile=mcp-app. Hosts that support MCP Apps render it inline; hosts that do not can
still read it as an HTML document.
Privacy
The server reads one local file (the one you name in AGENTHUB_STATE_FILE) and sends nothing
anywhere. See PRIVACY.md.
License
MIT — see LICENSE.
Available Tools
3 toolsget_statusARead-onlyIdempotent
Return the current pipeline state as structured JSON. Reads the file given by AGENTHUB_STATE_FILE if set; otherwise returns in-memory state, which is flagged with is_sample_data=true.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
show_agenthub_monitorARead-onlyIdempotent
Render the interactive pipeline dashboard inline in the host. Shows DAG node states and test-harness metrics from the configured state file, or built-in sample data when no state file is configured.
| Name | Required | Description | Default |
|---|---|---|---|
| view | No | View mode. | full |
trigger_actionAIdempotent
Record an action request in the server's in-memory state and return the updated state. This server does not execute commands, start jobs, or reach the network — it only annotates its own state so the dashboard can reflect a requested action.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | Action to record. |
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
v1.0.0- First observed
get_status - First observed
show_agenthub_monitor - First observed
trigger_action
TDQS
Scored across 3 tools
get_status and show_agenthub_monitor both surface the same pipeline state and could be confused at a glance, but they differ clearly in output form (structured JSON vs. rendered inline dashboard). trigger_action is distinct in that it only annotates state rather than reading it. The descriptions explicitly clarify these boundaries.
get_status and trigger_action follow a clean verb_noun pattern, while show_agenthub_monitor bakes the server name into the noun (show_<server>_monitor). This is a minor deviation but still readable and predictable in intent.
Three tools is on the thin side, but for a narrow monitor-and-annotate purpose each tool earns its place: read state, render dashboard, record an action request. No padding or redundant tools.
The surface covers reading and rendering state plus recording an action, but there is no way to clear or acknowledge a recorded action, and no per-node querying or filtering. These gaps leave agents at a dead end after triggering an action, though the core monitoring loop works.
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