
Postgres Scout Mcp
- Updated March 7, 2026
- bluwork/postgres-scout-mcp
Postgres Scout MCP is an MCP server that scouts PostgreSQL via MCP with read-only-by-default safety, monitoring, and data-quality focus.
About
Postgres Scout MCP gives MCP-enabled agents a disciplined way to explore PostgreSQL without treating every session like a superuser shell. developers on Supabase, RDS, or local Postgres frequently chase slow queries and constraint surprises through manual psql; Scout centralizes scouting, safety controls, monitoring alignment, and data-quality checks as tools the agent can reuse across incidents. Start in read-only mode for staging and production introspection, supply your PostgreSQL URI in server arguments, and switch to read-write only for deliberate maintenance. It sits in Operate when you are validating analytics tables, chasing migration side effects, or confirming row-level patterns—not when you are sketching an ERD on day one. Combine with SQL migration workflows and application logs for full-stack diagnosis.
- AI-assisted PostgreSQL scouting with built-in safety features
- Read-only default via --mode; read-write when you opt in
- postgresql:// connection URI passed as MCP package argument
- Data-quality and monitoring oriented scout workflows
- stdio npm postgres-scout-mcp v1.0.3
Postgres Scout Mcp by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
claude mcp add postgres-scout-mcp -- npx -y postgres-scout-mcp read-onlyAdd your badge
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| Package | postgres-scout-mcp |
|---|---|
| Transport | STDIO |
| Auth | None |
| Last updated | March 7, 2026 |
| Repository | bluwork/postgres-scout-mcp ↗ |
What it does
Connect your agent to PostgreSQL for safe scouting, monitoring hooks, and data-quality review on real connections.
Who is it for?
Best when you're running Postgres-backed SaaS or APIs and want agent-assisted DB diagnostics with conservative defaults.
Skip if: Projects not yet on Postgres, or regulated environments that forbid any agent database access regardless of mode.
What you get
Your agent scouts schemas and data quality through a gated MCP connection with explicit read-only versus read-write modes.
- Agent-executed Postgres scout and quality insights
- Documented read-only operational access pattern
- Optional read-write scouting when mode is explicitly changed
By the numbers
- Server version 1.0.3 (npm postgres-scout-mcp)
- 2 server modes: read-only (default) and read-write
- Default URI example: postgresql://localhost:5432/postgres
README.md
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 <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
Recommended MCP Servers
How it compares
Postgres operational scout MCP, not a migration generator or ORM scaffolding skill.
FAQ
Who is postgres-scout-mcp for?
Developers operating PostgreSQL (hosted or local) who use MCP clients and want guarded agent access for scouting and quality checks.
When should I use postgres-scout-mcp?
Use it when monitoring production or staging—investigating anomalies, verifying migrations, or reviewing data quality after releases.
How do I add postgres-scout-mcp to my agent?
Add postgres-scout-mcp as a stdio MCP server with your PostgreSQL URI; default --mode to read-only in production configs.