# Sports Context Protocol (npm · sports-context-protocol)

Self-learning operational context layer for AI sports agents. Profile 001: golf.

- Trust score: 67/100 (medium)
- Change this week: +19
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- npm · `sports-context-protocol`: 67/100 (this document), [markdown](https://verifymcp.io/servers/dswane-sports-context-protocol/sports-context-protocol.md), [page](https://verifymcp.io/servers/dswane-sports-context-protocol/sports-context-protocol)

## Channel facts

- Registry: `npm`
- Package: `sports-context-protocol`
- Version: `0.1.2`
- Transport: `stdio`

## Trust breakdown

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. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 87/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 72 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 81/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 859 tokens (~42/item across 20 items; 9 tools + 11 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 67/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 0% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add dswane-sports-context-protocol -- npx -y sports-context-protocol
```

### Codex

```bash
codex mcp add dswane-sports-context-protocol -- npx -y sports-context-protocol
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "dswane-sports-context-protocol": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "sports-context-protocol"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add dswane-sports-context-protocol --command npx --arg -y --arg sports-context-protocol
```

### Hermes

```yaml
mcp_servers:
  dswane-sports-context-protocol:
    command: "npx"
    args: ["-y", "sports-context-protocol"]
```

### Other

```json
{
  "mcpServers": {
    "dswane-sports-context-protocol": {
      "command": "npx",
      "args": [
        "-y",
        "sports-context-protocol"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-02 (score 66, +43)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Malware scan: unverified → pass
- [functional regression] Schema quality: 100 → unverified
- [functional regression] Security disclosure: fail → unverified
- [functional regression] Tool coverage: 100 → unverified
- [functional improvement] License: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Stability: unverified → 0.23
- [functional improvement] Schema quality: unverified → good
- [functional] Licence: MIT

### 2026-08-01 (score 23, +18)

- [functional improvement] Tool coverage: unverified → 100
- [functional improvement] Schema quality: unverified → 100

### 2026-07-31 (score 5, −25)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 30, −18)

- [security regression] Malware scan: pass → unverified

### 2026-07-27 (score 48)

First indexed and scored.

## MCP tools (9)

### `get_course_context` (~66 tokens)

Get course context

Returns the full operating context for the course: tee-sheet summary, inventory, booking and pricing policies, events, weather, pace risks, recent decisions, and learning insights. An agent should call this before acting.

Input parameters:

- `courseId` (string)
- `date` (string)

### `get_available_inventory` (~70 tokens)

Get available inventory

Finds available tee times near a preferred time. Never returns protected, booked, or blocked inventory as bookable.

Input parameters:

- `date` (string)
- `players` (integer)
- `preferredTime` (string)
- `publicAgent` (boolean)
- `timeWindowMinutes` (number)

### `check_booking_action` (~91 tokens)

Check booking action

Checks whether a booking is allowed, blocked, risky, or warns based on policy and learned memory. Writes a decision event to the ledger.

Input parameters:

- `agentId` (string)
- `courseId` (string)
- `date` (string)
- `now` (string)
- `players` (integer)
- `publicAgent` (boolean)
- `requestedStartTime` (string, required)

### `check_pricing_action` (~92 tokens)

Check pricing action

Checks whether a quoted or discounted price is allowed, given the absolute floor, time-window rate, discount limits, approval rules, and learned pricing patterns. Writes a decision event.

Input parameters:

- `agentId` (string)
- `courseId` (string)
- `currentPrice` (number, required)
- `date` (string)
- `proposedPrice` (number, required)
- `startTime` (string, required)

### `create_soft_hold` (~86 tokens)

Create soft hold

Creates a temporary hold on a tee time before confirmation. Marks the slot as soft_hold on the tee sheet.

Input parameters:

- `agentId` (string)
- `courseId` (string)
- `date` (string)
- `golferName` (string)
- `players` (integer)
- `startTime` (string)
- `teeTimeId` (string)

### `write_decision_event` (~125 tokens)

Write decision event

Logs a decision event to the ledger. Most decision tools write their own events; this tool is for agents that want to log an action directly.

Input parameters:

- `actionType` (string, required)
- `agentId` (string)
- `allowed` (boolean, required)
- `courseId` (string)
- `fingerprintKey` (string)
- `inputSummary` (string, required)
- `reasons` (array)
- `requiresApproval` (boolean)
- `resultSummary` (string, required)
- `riskLevel` (string)
- `toolName` (string, required)

### `submit_outcome_feedback` (~65 tokens)

Submit outcome feedback

The learning tool. Attaches an outcome to a past decision and updates SCP's learning memory so future similar decisions improve.

Input parameters:

- `decisionEventId` (string, required)
- `feedbackType` (string, required)
- `metrics` (object)
- `notes` (string)

### `get_learning_insights` (~56 tokens)

Get learning insights

Returns what SCP has learned: lessons, operator preferences, pricing and pace patterns, and similar past decisions. Optionally filtered to a decision fingerprint key.

Input parameters:

- `courseId` (string)
- `fingerprintKey` (string)

### `explain_action` (~60 tokens)

Explain action

Explains a decision result for a chosen audience: golfer (simple, no internal language), operator (operational detail), or developer (structured detail).

Input parameters:

- `actionType` (string, required)
- `audience` (string)
- `result` (object, required)

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/dswane-sports-context-protocol/sports-context-protocol#diagnostics

## Score history

- 2026-08-03: 67
- 2026-08-02: 66
- 2026-08-01: 23
- 2026-07-31: 5
- 2026-07-30: 30
- 2026-07-28: 48
- 2026-07-27: 48

## Links

- npm package: https://www.npmjs.com/package/sports-context-protocol
- Socket report: https://socket.dev/npm/package/sports-context-protocol
- Repository: https://github.com/Dswane/Sports-Context-Protocol
- Changelog RSS feed: https://verifymcp.io/servers/dswane-sports-context-protocol/sports-context-protocol/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/dswane-sports-context-protocol/sports-context-protocol/changelog.json
- HTML version of this page: https://verifymcp.io/servers/dswane-sports-context-protocol/sports-context-protocol