# Performix Site MCP server

Source: https://glimind.com/server/mcp-registry%2Fapp.performix%2Fperformix-site
Registry id: `mcp-registry/app.performix/performix-site`
Status: live (checked 2026-10-26T19:12:31.189Z)

## Verdict

Performix Site MCP server answered 99.95% of Glimind's liveness checks over 30 days, better than 37% of MCP servers, with 673 ms median handshake and 3 outages in 90 days. Its agent-readiness grade is A (96/100) across 10 tools, costing an agent about 1,903 tokens to load. Checked every few minutes; no tool is ever called.

## Measurements (30 days)

| Metric | Value | Better than |
|---|---|---|
| Uptime, 30 days | 99.95% | 37% of MCP servers |
| Median handshake latency | 673 ms | 39% of MCP servers |
| p95 handshake latency | 2823 ms | — |
| Checks in 30 days | 4,950 | — |
| Outages, 90 days | 3 | — |
| Median recovery | 6 min | — |
| Agent-readiness score | 96/100 (A) | 82% of MCP servers |
| Tools | 10 | — |
| Tool-list size for an agent | ~1,903 tokens | 53% of MCP servers |
| Days observed | 29 | — |

## Install

```json
{
  "mcpServers": {
    "performix-site-mcp-server": {
      "type": "http",
      "url": "https://performix.app/api/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http performix-site-mcp-server https://performix.app/api/mcp
```

## Tools (10)

- `get_book`: Get the full grounded profile for one book/cluster record by slug (from list_books): the record's own argument (contrast-not-summary) plus metadata and cross-li
- `get_evidence_source`: Get the full source → finding → construct → survey-item evidence chain for one source by id (from list_evidence_sources): its citation, every finding extracted 
- `get_guide_part`: Get the full body of one Team Performance Science Guide part by slug (from list_guide_parts). Same content rendered at performix.app/learn/<slug>. A part whose 
- `get_outcome_model`: Get one outcome's full driver table by id (from list_outcome_models): every driver's name, definition, CAMS dimension, lens role, evidence grade, study count (k
- `list_books`: List the performance-science reading corpus behind Performix — book/cluster profiles, each with a stance toward the CAMS diagnostic thesis (ally, orthodoxy, mix
- `list_evidence_sources`: List the 196 source records behind Performix's Performance Science Library — each a book, paper or corpus item with at least one derived finding, plus which CAM
- `list_guide_parts`: List all 12 parts (8 numbered parts + 4 appendices) of the Team Performance Science Guide, Performix's cited public reference on why team performance varies and
- `list_outcome_models`: List the constructed outcome-model register behind Performix diagnostics — 28 per-outcome factor models generated from principia's meta-analytic library, each w
- `self_diagnose_book`: The runnable library's weakest-lever read, computed here from the committed book model: rate how present each of the book's levers is on your team (1–5) and get
- `situation_demo_get`: Get a committed situation-demo export for an outcome and audience seat. The data is synthetic and illustrative, never a real client or live measurement. Visual 

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.