Postgres Scout MCP
概览
作者提供的说明(英文原文)
Scout your PostgreSQL databases with AI - safety features, monitoring, and data quality
PopNx MCP 的三大支柱
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
- 用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
- 我们的基础检查i1 项中通过 1 项依据公开信息检查;尚未扫描代码
- 使用情况i非常新↓ 55/周 · ★ –
它能帮你做什么
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
- 连接方式: 在你的电脑上运行
- 传输方式: stdio
- 分类: 数据库与数据集
安装
选择你使用的 AI 应用,然后复制设置。
安装之前
- 基础检查:1 项中通过 1 项
- 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
- 注册中心没有列出需要填写的密钥。
你需要
- npm已安装 Node.js(用于 npx 命令)
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"postgres-scout": {
"command": "npx",
"args": [
"-y",
"postgres-scout-mcp",
"read-only",
"postgresql://localhost:5432/postgres"
]
}
}
}在终端中运行这条命令
claude mcp add postgres-scout -- npx -y postgres-scout-mcp read-only postgresql://localhost:5432/postgres或者自己复制设置
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"postgres-scout": {
"command": "npx",
"args": [
"-y",
"postgres-scout-mcp",
"read-only",
"postgresql://localhost:5432/postgres"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
或者自己复制设置
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"postgres-scout": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"postgres-scout-mcp",
"read-only",
"postgresql://localhost:5432/postgres"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
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。
它能做什么
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。
基础检查i
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9日
- ✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 bluwork 验证,该账户拥有此仓库
- … 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
- … 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
- – 不适用
端点有响应
它在你的电脑上运行,没有互联网端点
- – 不适用
使用 OAuth 登录
在你的电脑上运行,改用本地设置
- … 尚未检查
工具描述中没有隐藏指令
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
与“数据库与数据集”中的其他服务器比较i
- 星标数多于此分类中其他 1151 个服务器的 0%
- 发布到注册中心的时间比此分类中其他 1151 个服务器的 5% 更新
- 基础检查结果等于或优于此分类中其他 1151 个服务器的 100%
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。
常见问题
Postgres Scout MCP 安全吗?
它在 1 项适用的基础检查中通过了 1 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。
它需要哪些密钥或代码?
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。
它在我的电脑上运行还是在云端?
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)。
它还在维护吗?
GitHub 仓库最后更新于–,最新版本(1.0.3)于8个月前进入注册中心。
哪些应用可以使用它?
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。
有什么可以替代它?
同一分类中有:Supabase, MongoDB MCP Server, Elasticsearch MCP Server
替代选择
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
作者的 README
打开 README
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。
Postgres Scout MCP
Scout your PostgreSQL databases with AI - A production-ready Model Context Protocol server with built-in safety features, monitoring, and data quality tools.
What You Get
You ask:
*"How healthy is my production database? Any urgent issues?"*
Postgres Scout returns:
Overall Health Score: 78/100
Component Breakdown
| Component | Score | Status |
|---|---|---|
| Cache Performance | 94/100 | Healthy |
| Index Efficiency | 82/100 | Good |
| Table Bloat | 61/100 | Needs Attention |
| Connection Usage | 75/100 | Fair |
Issues Found
- HIGH — Table
ordershas 34% bloat (2.1 GB wasted). VACUUM FULL recommended. - MEDIUM — 3 unused indexes on
sessionsconsuming 890 MB. - LOW — Cache hit ratio for
analytics_eventsis 71% (target: >90%).
Recommendations
- Run
VACUUM FULL ordersduring maintenance window - Drop unused indexes:
idx_sessions_legacy,idx_sessions_old_token,idx_sessions_temp - Consider adding
analytics_eventsto shared_buffers or partitioning by date
That's getHealthScore — one of 38 tools covering exploration, diagnostics, optimization, monitoring, data quality, and safe writes.
Quick Start
Claude Code
claude mcp add postgres-scout -- npx -y postgres-scout-mcp postgresql://localhost:5432/mydb
Then ask: *"Show me the largest tables and whether they have any bloat issues."*
Claude Desktop
Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": { "postgres-scout": { "command": "npx", "args": ["-y", "postgres-scout-mcp", "postgresql://localhost:5432/mydb"], "type": "stdio" } } }
Cursor / VS Code
Add to your MCP settings:
{
"postgres-scout": { "command": "npx", "args": ["-y", "postgres-scout-mcp", "postgresql://localhost:5432/mydb"] } }
Read-Only vs Read-Write
The server runs in read-only mode by default. For write operations, run a separate instance:
{
"mcpServers": { "postgres-scout-readonly": { "command": "npx", "args": ["-y", "postgres-scout-mcp", "--read-only", "postgresql://localhost:5432/production"], "type": "stdio" }, "postgres-scout-readwrite": { "command": "npx", "args": ["-y", "postgres-scout-mcp", "--read-write", "postgresql://localhost:5432/development"], "type": "stdio" } } }
- postgres-scout-readonly: Safe exploration, no risk of data modification
- postgres-scout-readwrite: Write operations when explicitly needed
Tools
Explore — understand your database
listDatabases— databases the user has access togetDatabaseStats— size, cache hit ratio, connection infolistSchemas— all schemas in the current databaselistTables— tables with size and row statisticsdescribeTable— columns, constraints, indexes, and more
Query — run and analyze
executeQuery— run SELECT queries (or writes in read-write mode)explainQuery— EXPLAIN plans for performance analysisoptimizeQuery— optimization recommendations for a specific query
Diagnose — find problems before they find you
getHealthScore— overall health score with component breakdowndetectAnomalies— anomalies in performance, connections, and dataanalyzeTableBloat— bloat analysis for VACUUM planninggetSlowQueries— slow query analysis (requires pg_stat_statements)suggestVacuum— VACUUM recommendations based on dead tuples and bloat
Optimize — make it faster
suggestIndexes— missing index recommendations from query patternssuggestPartitioning— partitioning strategies for large tablesgetIndexUsage— identify unused or underused indexes
Monitor — watch it live
getCurrentActivity— active queries and connectionsanalyzeLocks— lock contention and blocking queriesgetLiveMetrics— real-time metrics over a time windowgetHottestTables— tables with highest activitygetTableMetrics— comprehensive per-table I/O and scan stats
Data Quality — trust your data
findDuplicates— duplicate rows by column combinationfindMissingValues— NULL analysis across columnsfindOrphans— orphaned records with invalid foreign keyscheckConstraintViolations— test constraints before adding themanalyzeTypeConsistency— type inconsistencies in text columns
Relationships — follow the connections
exploreRelationships— multi-hop foreign key traversalanalyzeForeignKeys— foreign key health and performance
Time Series — temporal analysis
findRecent— rows within a time windowanalyzeTimeSeries— window functions and anomaly detectiondetectSeasonality— seasonal pattern detection
Export — get data out
exportTable— CSV, JSON, JSONL, or SQLgenerateInsertStatements— INSERT statements for migration
Write (read-write only) — safe modifications
previewUpdate/previewDelete— see what would change before committingsafeUpdate— UPDATE with dry-run, row limits, empty WHERE protectionsafeDelete— DELETE with dry-run, row limits, empty WHERE protectionsafeInsert— INSERT with validation, batching, ON CONFLICT support
Security
- Read-only by default — write operations must be explicitly enabled
- All queries use parameterized values
- SQL injection prevention with input validation and pattern detection
- Identifier sanitization for table/column names
- Rate limiting on all operations
- Query timeouts to prevent long-running queries
- Response size limits to prevent memory exhaustion
Examples
*"What are the largest tables and do they have bloat?"*
listTables({ schema: "public" })
analyzeTableBloat({ schema: "public", minSizeMb: 100 })
*"Find duplicate emails in the users table."*
findDuplicates({ table: "users", columns: ["email"] })
*"Which queries are slowest and how can I speed them up?"*
getSlowQueries({ minDurationMs: 100, limit: 10 })
suggestIndexes({ schema: "public" })
*"Show me what's happening on the database right now."*
getCurrentActivity()
getLiveMetrics({ metrics: ["queries", "connections", "cache"], duration: 30000, interval: 1000 }) getHottestTables({ limit: 5, orderBy: "seq_scan" })
*"Find orphaned orders that reference deleted customers."*
findOrphans({ table: "orders", foreignKey: "customer_id", referenceTable: "customers", referenceColumn: "id" })
Configuration
| Variable | Default | Description |
|---|---|---|
QUERY_TIMEOUT | 30000 | Query timeout in milliseconds |
MAX_RESULT_ROWS | 10000 | Maximum rows returned per query |
ENABLE_RATE_LIMIT | true | Enable rate limiting |
RATE_LIMIT_MAX_REQUESTS | 100 | Requests per window |
RATE_LIMIT_WINDOW_MS | 60000 | Rate limit window (ms) |
PGMAXPOOLSIZE | 10 | Connection pool max size |
PGMINPOOLSIZE | 2 | Connection pool min size |
PGIDLETIMEOUT | 10000 | Idle connection timeout (ms) |
ENABLE_LOGGING | false | Enable file logging |
LOG_DIR | ./logs | Log file directory |
LOG_LEVEL | info | Log verbosity: debug, info, warn, error |
CLI flags: --read-only (default), --read-write, --mode
Logging
File logging is disabled by default. Set ENABLE_LOGGING=true to enable. Two log files are created in LOG_DIR:
- tool-usage.log — every tool call with timestamp, name, and arguments
- error.log — errors with stack traces
Connection strings are automatically redacted in all output.
Development
git clone https://github.com/bluwork/postgres-scout-mcp.git
cd postgres-scout-mcp pnpm install pnpm build pnpm test
License
Apache-2.0