# Buzzr Sports Engine (npm · @buzzr/mcp)

Local sports math, DFS settlement, bet analytics, and game-entertainment tools.

- Trust score: 73/100 (medium)
- Change this week: +49
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- npm · `@buzzr/mcp`: 73/100 (this document), [markdown](https://verifymcp.io/servers/buzzr-app-dfs-engine/buzzr-mcp.md), [page](https://verifymcp.io/servers/buzzr-app-dfs-engine/buzzr-mcp)

## Channel facts

- Registry: `npm`
- Package: `@buzzr/mcp`
- Version: `5.1.0`
- 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**: 88/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (97 of 101), 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 (97 of 101), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 97/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to Buzzr-app/dfs-engine).
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 17 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 43/100
  - AI-judged instruction clarity (poor).
  - Context-footprint check failed: tool/resource definitions use about 1314 tokens (~119/item across 11 items; 11 tools + 0 resources), over budget; trim descriptions and params.
  - 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**: 92/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 77% 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 buzzr-app-dfs-engine -- npx -y @buzzr/mcp
```

### Codex

```bash
codex mcp add buzzr-app-dfs-engine -- npx -y @buzzr/mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "buzzr-app-dfs-engine": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@buzzr/mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add buzzr-app-dfs-engine --command npx --arg -y --arg @buzzr/mcp
```

### Hermes

```yaml
mcp_servers:
  buzzr-app-dfs-engine:
    command: "npx"
    args: ["-y", "@buzzr/mcp"]
```

### Other

```json
{
  "mcpServers": {
    "buzzr-app-dfs-engine": {
      "command": "npx",
      "args": [
        "-y",
        "@buzzr/mcp"
      ]
    }
  }
}
```

## 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 73, −2)

No change was recorded against any check on this day. Supply Chain Security went from 97 to 88. Other categories moved too: Stability & Change Management rose 4.

### 2026-08-02 (score 75, +40)

- [security improvement] Install scripts: unverified → pass
- [security improvement] Provenance: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security] The attested source repository moved: Buzzr-app/dfs-engine
- [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 → poor
- [functional] Licence: MIT

### 2026-08-01 (score 35, +15)

- [security improvement] Malware scan: unverified → pass

### 2026-07-31 (score 20, −7)

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

### 2026-07-30 (score 27, −18)

- [security regression] Malware scan: pass → unverified

### 2026-07-28 (score 45, +21)

- [functional regression] Security disclosure: unverified → fail
- [functional improvement] Tool coverage: unverified → 100
- [functional] First check of Tool coverage: 77
- [functional] First check of Schema quality: unverified
- [functional] First check of Schema quality: fail
- [functional] First check of Schema quality: fail

### 2026-07-27 (score 24)

First indexed and scored.

## MCP tools (11)

### `grade_dfs_entry` (~229 tokens)

Grade DFS entry

Settle a DFS pick-em entry (PrizePicks/Underdog style) with @buzzr/dfs-engine. Applies the book policy (ties, DNPs, flex payouts), returns the entry status, payout split, per-leg decisions, and explanation codes.

Input parameters:

- `actualsByLegId` (object): Optional map of legId to observed stat value, merged in at settlement time.
- `baseMultiplier`
- `bookId` (string, required): DFS book id, e.g. "prizepicks" or "underdog". See list_book_policies.
- `displayedMultiplier` (number, required): The payout multiplier the book displayed at entry time.
- `entryId` (string, required): Stable id for the entry being graded.
- `legs` (array, required)
- `placedAt`: ISO timestamp the entry was placed.
- `playTypeId` (string, required): Play type id for the book, e.g. "power", "flex", "underdog_standard".
- `profitBoostPct`
- `stake` (number, required): Entry stake in currency units.

### `grade_dfs_entries` (~64 tokens)

Grade DFS entries

Settle up to 50 DFS entries with @buzzr/dfs-engine batch settlement. Returns full explainable settlement results, isolated serializable failures, summary counts, and per-call stat-cache metrics.

Input parameters:

- `concurrency` (integer)
- `entries` (array, required)

### `validate_dfs_entry` (~99 tokens)

Validate DFS entry

Run the @buzzr/dfs-engine runtime validators against a candidate DFS entry. Returns ok plus structured error/warning issues (code, message, path, legIds) without settling anything.

Input parameters:

- `entry` (object, required): A candidate DfsEntryInput object (entryId, bookId, playTypeId, stake, displayedMultiplier, legs[]). Passed as-is to the engine validators so malformed entries return structured issues instead of sche…

### `list_book_policies` (~49 tokens)

List DFS book policies

Enumerate registered executable DFS compatibility policies from the engine and published draft fixtures that are metadata-only. Includes version, effective date, verification, source references, complete play-type metadata, and executable status.

### `fair_line` (~116 tokens)

No-vig fair line

Remove the vig from a two-sided market with @buzzr/bets-core. Given the offered American odds for both sides, returns the fair win probability, fair American odds, market overround, and the edge of the selected price versus fair.

Input parameters:

- `opposite` (number, required): American odds offered for the other side of the same market.
- `selected` (number, required): American odds offered for the side you are evaluating.
- `selectedSide` (string): Optional label for the selected side, e.g. "Lakers -3.5".

### `closing_line_value` (~72 tokens)

Closing line value

Compare placed and closing American odds with @buzzr/bets-core. Returns the implied-probability delta in percentage points and whether the bet beat the close.

Input parameters:

- `closingAmericanOdds` (number, required): American odds when the market closed.
- `placedAmericanOdds` (number, required): American odds when the bet was placed.

### `parlay_value` (~129 tokens)

Parlay fair value

Price a parlay with @buzzr/bets-core: removes the vig from each leg, combines the fair leg probabilities into a fair parlay price, and reports the edge of the offered combined odds. With a stake, also returns expected profit and expected ROI.

Input parameters:

- `legs` (array, required): Every leg of the parlay, each with both sides of its market.
- `offeredAmericanOdds` (number): Combined parlay price the book is offering. Defaults to the product of the selected leg prices when omitted.
- `stake` (number): Optional stake; adds expected-value math to the result.

### `kelly_stake` (~125 tokens)

Kelly stake sizing

Kelly-criterion stake sizing with @buzzr/bets-core. Returns the full Kelly bankroll fraction (clamped at 0 for -EV bets), the fractional-Kelly recommendation, and the recommended stake for the given bankroll.

Input parameters:

- `americanOdds` (number, required): American odds offered for the bet.
- `bankroll` (number, required): Total bankroll in currency units.
- `fraction` (number): Fraction of full Kelly to recommend. Defaults to 0.25 (quarter-Kelly).
- `winProbability` (number, required): Your estimated win probability, strictly between 0 and 1.

### `summarize_bet_history` (~62 tokens)

Summarize bet history

Summarize up to 500 bet records with @buzzr/bets-core. Returns the overall rollup, UTC period buckets, maximum drawdown, and win/loss streaks.

Input parameters:

- `bets` (array, required)
- `period` (string)

### `predict_game_buzz` (~283 tokens)

Predict game buzz

Predict how entertaining a game will be (1-10 buzz score) with the @buzzr/entertainment-engine ML model. Returns the score, model confidence, and the weighted factors behind the prediction. Odds, team power, injuries, and narrative context sharpen the estimate.

Input parameters:

- `awayTeam` (string, required)
- `engagement` (object): Fan engagement signals for the matchup.
- `gameType`: Regular season, play-in, or playoff.
- `homeTeam` (string, required)
- `injuries` (object): Injury impact per team.
- `league` (string, required): League code, e.g. "NBA", "NFL", "EPL", "WC".
- `narratives` (object): Narrative flags that boost buzz (rivalries, debuts, revenge games).
- `odds` (object): Betting-market context for the game.
- `searchHeat` (object): Per-team search interest in [-1, 1].
- `starPower`: Marquee player availability / skill density in [0, 1].
- `startsAt` (string, required): ISO 8601 kickoff/tip-off time, e.g. "2026-07-06T19:30:00Z".
- `status` (string): Game status. The model only predicts games that are not in progress.
- `teamPower` (object): Team power ratings.

### `rank_games` (~86 tokens)

Rank games for a user

Rank candidate games for a specific user with @buzzr/entertainment-engine v5: base entertainment score plus bounded personal-affinity and social adjustments. Returns the ranked list with per-game factor breakdowns.

Input parameters:

- `games` (array, required)
- `limit` (integer): Return only the top N games.
- `profile` (object, required): The user taste profile used to personalize the ranking.

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/buzzr-app-dfs-engine/buzzr-mcp#diagnostics

## Score history

- 2026-08-03: 73
- 2026-08-02: 75
- 2026-08-01: 35
- 2026-07-31: 20
- 2026-07-30: 27
- 2026-07-28: 45
- 2026-07-27: 24

## Links

- npm package: https://www.npmjs.com/package/@buzzr/mcp
- Socket report: https://socket.dev/npm/package/@buzzr/mcp
- Repository: https://github.com/Buzzr-app/dfs-engine
- Website: https://buzzr-app.github.io/dfs-engine/
- Changelog RSS feed: https://verifymcp.io/servers/buzzr-app-dfs-engine/buzzr-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/buzzr-app-dfs-engine/buzzr-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/buzzr-app-dfs-engine/buzzr-mcp