Honcho
Memory that reasons: continual learning for stateful agents. Better context, fewer tokens.
Local sports math, DFS settlement, bet analytics, and game-entertainment tools.
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
需要先在电脑上安装 Node.js(只需一次) · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
SettingsDeveloperEdit Config
{
"mcpServers": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}用 Buzzr Sports Engine 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Buzzr Sports Engine,或回答中出现 Buzzr Sports Engine 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Buzzr Sports Engine
Buzzr Sports Engine 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
A · 使用能连接 Buzzr Sports Engine 的应用
B · 游戏、体育、美食与学习 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
可连接 Claude Code,但需要先准备
需要先在电脑上安装 Node.js(只需一次)
Mac:按 Command+空格,输入 Terminal · Windows:打开 PowerShell
claude mcp add --scope user dfs-engine -- npx -y @buzzr/mcp应能看到 Buzzr Sports Engine 在列表中并显示已连接
用 Buzzr Sports Engine 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude Code 说正在使用 Buzzr Sports Engine,或回答中出现 Buzzr Sports Engine 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
可连接 Cursor,但需要先准备
需要先在电脑上安装 Node.js(只需一次)
用 Buzzr Sports Engine 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Cursor 说正在使用 Buzzr Sports Engine,或回答中出现 Buzzr Sports Engine 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Cursor 帮助页面核实 · 你的界面可能因版本略有不同
可连接 VS Code,但需要先准备
需要先在电脑上安装 Node.js(只需一次)
用 Buzzr Sports Engine 告诉我你能帮我做什么,然后做一件给我看✓ 如果 VS Code 说正在使用 Buzzr Sports Engine,或回答中出现 Buzzr Sports Engine 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 VS Code 帮助页面核实 · 你的界面可能因版本略有不同
Claude Code
claude mcp add --scope user dfs-engine -- npx -y @buzzr/mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"dfs-engine": {
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"dfs-engine": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@buzzr/mcp"
]
}
}
}这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月13日
注册名称已通过 GitHub 账户 Buzzr-app 验证,该账户拥有此仓库
代码最后更新于2个月前
使用 MIT
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于2个月前,最新版本(5.1.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Honcho, ShipSwift, Pm Claude Skills
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Memory that reasons: continual learning for stateful agents. Better context, fewer tokens.
1310 professional Agent Skills + workflow recipes — searchable & fetchable over MCP.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
MCP server exposing the @buzzr sports engines to AI agents — DFS settlement, odds math, and entertainment predictions as tools.
@buzzr/mcp is a Model Context Protocol stdio server that puts the whole @buzzr engine family in front of any MCP-capable agent (Claude Desktop, Claude Code, or your own client). All math and policy logic lives in the underlying engines — this package is a thin, schema-validated tool surface:
@buzzr/dfs-engine — pick-em settlement with versioned compatibility and custom policies@buzzr/bets-core — no-vig fair lines, parlay pricing, expected value, Kelly staking@buzzr/entertainment-engine — ML buzz-score predictions and personalized game rankingRun it directly with npx (Node 22+). Pin the version you reviewed instead of silently accepting a future latest release:
npx -y @buzzr/mcp@5.1.0
The server speaks MCP over stdio: JSON-RPC on stdin/stdout, logs on stderr. It exposes 11 tools with bounded inputs and outputs, and does not fetch live odds, box scores, operator accounts, or private user data.
The Buzzr Sports Engine listing on Smithery packages the exact published @buzzr/mcp@5.1.0 artifact as a local stdio MCPB. It is a distribution and installation surface, not a hosted HTTP service. To add it to Codex through Smithery:
npx -y smithery@1.2.0 mcp add sarveshsea/buzzr-sports-engine --client codex
Smithery writes the corresponding MCP configuration for the selected client. Use the direct npm command above when you need both the server package and its launcher configuration pinned explicitly.
Add this to claude_desktop_config.json from Settings → Developer → Edit Config, then fully quit and reopen Claude Desktop:
{
"mcpServers": { "buzzr": { "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"] } } }
claude mcp add --transport stdio buzzr -- npx -y @buzzr/mcp@5.1.0
For a version-controlled project configuration, add this to .mcp.json, trust the project when prompted, and start a new Claude Code session:
{
"mcpServers": { "buzzr": { "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"] } } }
Confirm it with claude mcp get buzzr; inside Claude Code, /mcp shows the connection and discovered tool count.
Add this to the repository's .cursor/mcp.json (or the equivalent user-level MCP configuration), then fully restart Cursor:
{
"mcpServers": { "buzzr": { "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"] } } }
Open Cursor Settings → MCP to confirm buzzr connected and exposed 11 tools. See Cursor's MCP documentation if your installed Cursor version presents a different settings location.
The Codex CLI, IDE extension, and app share config.toml. The one-command user setup is:
codex mcp add buzzr -- npx -y @buzzr/mcp@5.1.0
Or add the equivalent block to ~/.codex/config.toml for all projects, or to a trusted repository's .codex/config.toml for that project only:
[mcp_servers.buzzr]
command = "npx" args = ["-y", "@buzzr/mcp@5.1.0"]
Run codex mcp get buzzr, then start a new Codex task after changing the configuration.
Use this process configuration in any client that accepts a command plus args:
{
"name": "buzzr", "transport": "stdio", "command": "npx", "args": ["-y", "@buzzr/mcp@5.1.0"], "env": {} }
Treat stdout as JSON-RPC only, read diagnostics from stderr, and close the child process's stdin during shutdown. The client must perform the MCP lifecycle below; starting npx in a terminal and seeing it remain open is normal for a stdio server waiting for a client.
The client sends initialize first. Verify the serverInfo.name field is "buzzr", the serverInfo.version field is the installed package version, and the response has a capabilities.tools object. Send notifications/initialized, then call tools/list. The server returns the 11 tools in the catalog below with their input schemas. It does not advertise data fetching, resources, or prompts.
examples/mcp-calls.json is a machine-readable JSON-RPC transcript with the initialization expectation, exact tool discovery order, and a safe list_book_policies → validate_dfs_entry → grade_dfs_entry workflow. The repository replays that workflow through a real MCP client in CI.
node --version, npm --version, and npx --version.npm view @buzzr/mcp@5.1.0 version, then run npm cache verify. If npm reports cache corruption, repair npm's cache before retrying; npm cache clean --force is a last resort because it removes the whole local cache.PATH than an interactive shell. On macOS or Linux, run command -v npx; on Windows, run where.exe npx. If the client cannot find npx, use that absolute path as command (normally npx.cmd on Windows) or launch the client from an environment where Node is on PATH.listening on stdio diagnostic to stderr and waits for JSON-RPC input.| Tool | Engine | What it does |
|---|---|---|
grade_dfs_entry | @buzzr/dfs-engine | Settle one transport-bounded 1–12-leg entry; executable built-in policies currently allow at most 6 PrizePicks or 8 Underdog legs. |
grade_dfs_entries | @buzzr/dfs-engine | Settle 1–50 entries, up to 600 total legs, with bounded concurrency and isolated failures. |
validate_dfs_entry | @buzzr/dfs-engine | Return structured engine validation issues for a candidate entry without settling it. |
list_book_policies | @buzzr/dfs-engine | List authoritative executable profile snapshots and metadata-only drafts, including status, verification, sources, and complete play types. |
fair_line | @buzzr/bets-core | Remove vig from both sides of one two-way market. |
closing_line_value | @buzzr/bets-core | Compare placed and closing prices for the same selection. |
parlay_value | @buzzr/bets-core | Price independent parlay legs, compare offered odds, and optionally calculate expected value. |
kelly_stake | @buzzr/bets-core | Calculate full and fractional Kelly stakes from a supplied win probability. |
summarize_bet_history | @buzzr/bets-core | Summarize up to 500 bets with overall and UTC-period rollups, drawdown, and streaks. |
predict_game_buzz | @buzzr/entertainment-engine | Predict one game's 1–10 entertainment score with confidence and factor detail. |
rank_games | @buzzr/entertainment-engine | Rank 1–100 candidate games for a bounded taste profile. |
Tool strings, identifiers, arrays, stdio frames, concurrent calls, and serialized results are bounded. American odds must be within [-100000, -100] or [100, 100000]. grade_dfs_entries, closing_line_value, and summarize_bet_history return string contractVersion: "1".
Operator-named policies are independent compatibility profiles, not official rules engines or evidence of affiliation:
Displayed lineup terms are authoritative. Call list_book_policies before grading, inspect verification and sources, and obtain explicit operator rulings for DNPs, reboots, ties, rescues, voids, and corrections. The tool lists future fixtures with executable: false; grading tools reject draft book IDs because drafts are metadata, not settlement implementations.
invalid_input result through an MCP client transport or a direct exported tool.handler(...) call. At most eight compact validation issues are included; raw Zod errors are never returned.tools/call request with invalid tool arguments.validate_dfs_entry intentionally accepts a bounded candidate object and returns the engine's structured validation report.isError: true results such as tool_execution_failed, entry_settlement_failed, server_busy, or result_too_large. Internal error details are not public."Did my PrizePicks slip hit?"
User: I had a $10 2-pick power play: LeBron over 25.5 points (he scored 31)
and Curry over 27.5 (he scored 33). What's the payout?
Agent calls
grade_dfs_entry:
`json
{
"entryId": "slip-1",
"bookId": "prizepicks",
"playTypeId": "power",
"stake": 10,
"displayedMultiplier": 3,
"legs": [
{ "legId": "l1", "playerName": "LeBron James", "league": "NBA", "propType": "points", "line": 25.5, "direction": "over", "actual": 31 },
{ "legId": "l2", "playerName": "Stephen Curry", "league": "NBA", "propType": "points", "line": 27.5, "direction": "over", "actual": 33 }
]
}
`
Result:
"status": "won","payout": { "total": 30, "withdrawable": 30, "bonus": 0 }—
both supplied actuals clear their lines and the submitted 3× displayed multiplier
is consistent with the selected compatibility table. Confirm the actual entry
details before tr