io.github.joepangallo/mcp-server-agent-analytics
NPM · MCP-SERVER-AGENT-ANALYTICS · SCANNED AUG 3
Track AI agent fleet performance, costs, anomalies, and trends.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score →
Supply Chain Security87
- No malware found by supply-chain analysis.Pass
- Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.Partial
- No install/post-install scripts declared.Pass
- Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency19
- Repository check failed: the declared repository URL returned HTTP 404. See how to fix → View diagnostics → Fail
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 154 days ago).Pass
- Security-disclosure policy not yet verified: we couldn't inspect the source repository.Unverified
Schema Quality & AI Usability77
- AI-judged instruction clarity (excellent).Pass
- Tool/resource definitions use about 483 tokens (~69/item across 7 items; 7 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
- Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
npm · mcp-server-agent-analytics
claude mcp add joepangallo-mcp-server-agent-analytics -- npx -y mcp-server-agent-analytics
codex mcp add joepangallo-mcp-server-agent-analytics -- npx -y mcp-server-agent-analytics
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"joepangallo-mcp-server-agent-analytics": {
"type": "local",
"command": [
"npx",
"-y",
"mcp-server-agent-analytics"
],
"enabled": true
}
}
} openclaw mcp add joepangallo-mcp-server-agent-analytics --command npx --arg -y --arg mcp-server-agent-analytics
mcp_servers:
joepangallo-mcp-server-agent-analytics:
command: "npx"
args: ["-y", "mcp-server-agent-analytics"] {
"mcpServers": {
"joepangallo-mcp-server-agent-analytics": {
"command": "npx",
"args": [
"-y",
"mcp-server-agent-analytics"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 3 Aug 26 +4
- Stability: unverified → 0.27 ▲ functional
- 2 Aug 26 +28
- Known CVEs: unverified → partial ▲ security
- Malware scan: unverified → pass ▲ security
- Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet. security
- Tool coverage: 100 → unverified ▼ functional
- Capabilities: pass → unverified ▼ functional
- Schema quality: unverified → excellent ▲ functional
- First check of Schema quality: unverified functional
- 1 Aug 26 +16
- Provenance: unverified → fail ▼ security
- Install scripts: unverified → pass ▲ security
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- License: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
- Maintenance: unverified → pass ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Licence: MIT functional
- 31 Jul 26 −6
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 30 Jul 26 −18
- Malware scan: pass → unverified ▼ security
- 27 Jul 26 40
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 3 Aug 2026 · Analysed npm/[email protected]
Provenance none
Ecosystem: npm · Outcome: none
Dependencies 95 packages
95 packages in the resolved dependency tree · 95 deprecated · 29 stale.
The dependency tree was only partially resolved, so these counts may be incomplete.
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
agent_insights ~62
Get deep insights for a specific AI agent — top queries, unhandled intents, latency stats (avg + P95), token usage, cost estimate, daily volume, and user feedback summary.
| Name | Type | Req | Description |
|---|---|---|---|
| agent_id | string | yes | The agent ID to get insights for |
No output schema declared.
No examples provided.
analytics_dashboard ~63
Get a fleet-wide analytics dashboard for all AI agents. Returns total events, unique agents, success rate, token usage, cost estimates, per-agent breakdowns, trending topics, and daily volume.
| Name | Type | Req | Description |
|---|---|---|---|
| days | number | — | Time range in days (default: 30) |
No output schema declared.
No examples provided.
compare_agents ~54
Compare two agents side by side on key metrics: event volume, success rate, latency, token usage, and cost.
| Name | Type | Req | Description |
|---|---|---|---|
| agent1 | string | yes | First agent ID |
| agent2 | string | yes | Second agent ID |
No output schema declared.
No examples provided.
detect_anomalies ~32
Check for anomalies across the agent fleet — error rate spikes, latency degradation, and unusual patterns compared to baseline.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
list_agents ~26
List all registered AI agents with their total events, success rate, and last seen timestamp.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
query_events ~98
Query stored agent events with optional filters. Returns raw event data for analysis.
| Name | Type | Req | Description |
|---|---|---|---|
| agent_id | string | — | Filter by agent ID |
| days | number | — | Time range in days |
| event_type | string | — | Filter by event type (e.g. 'query_completed') |
| limit | number | — | Max events to return (default: 50, max: 1000) |
| success | boolean | — | Filter by success status |
No output schema declared.
No examples provided.
track_event ~148
Ingest a new agent interaction event. Use this to track queries, completions, errors, and feedback for any AI agent.
| Name | Type | Req | Description |
|---|---|---|---|
| agent_id | string | yes | The agent that generated this event |
| error | string | — | Error message if the interaction failed |
| event_type | string | — | Event type (e.g. 'query_completed', 'error', 'feedback') |
| latency_ms | number | — | Response latency in milliseconds |
| prompt_tokens | number | — | Number of prompt tokens used |
| query | string | — | The query or task that was processed |
| response_tokens | number | — | Number of response tokens used |
| success | boolean | — | Whether the interaction was successful |
No output schema declared.
No examples provided.