MCP PostgreSQL Server

v0.6.2

Anthropic (Archived)

MCPdatabasesqlmcpmodel-context-protocol
79
Strong
About This MCP

ARCHIVED: Former official MCP server for PostgreSQL database interaction. This server is NO LONGER MAINTAINED and has been moved to servers-archived repository. No security updates provided. Community alternatives available. Use with caution.

Last Evaluated: November 9, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+
query execution accuracy

Query execution testing

Evidence
PostgreSQL Driver Integration — Uses standard PostgreSQL drivers with high query accuracy
highVerified: 2025-11-09
schema introspection

Schema discovery testing

Evidence
MCP Postgres Implementation — Comprehensive schema inspection including tables, columns, indexes, and constraints
highVerified: 2025-11-09
connection stability

Connection reliability testing

Evidence
PostgreSQL Reliability — Built on PostgreSQL's robust connection pooling and stability
highVerified: 2025-11-09
large result handling

Large dataset performance testing

Evidence
MCP Server Implementation — Handles large result sets with pagination and limits
mediumVerified: 2025-11-09
error handling

Error scenario testing

Evidence
PostgreSQL Error Reporting — Detailed error messages from PostgreSQL with proper propagation
highVerified: 2025-11-09
🛡️Security
+
sql injection protection

SQL injection testing

Evidence
Parameterized Queries — Uses parameterized queries to prevent SQL injection
highVerified: 2025-11-09
access control

Permission boundary testing

Evidence
PostgreSQL Permissions — Inherits database user permissions but AI can execute any query within those permissions
mediumVerified: 2025-11-09
data modification risk

Write operation risk assessment

Evidence
Security Analysis — AI can execute INSERT, UPDATE, DELETE operations if database user has permissions
highVerified: 2025-11-09
credential security

Credential storage review

Evidence
Connection String Management — Credentials stored in configuration; requires secure credential management
mediumVerified: 2025-11-09
audit logging

Logging capabilities assessment

Evidence
PostgreSQL Logging — Depends on PostgreSQL audit configuration; MCP server provides basic query logging
mediumVerified: 2025-11-09
🔒Privacy & Compliance
+
data exposure risk

Data flow and exposure analysis

Evidence
Data Flow Analysis — Query results including sensitive data sent to LLM provider
highVerified: 2025-11-09
pii protection

Privacy controls assessment

Evidence
MCP Security Guidelines — No built-in PII detection, redaction, or anonymization
highVerified: 2025-11-09
query result filtering

Data filtering capabilities review

Evidence
MCP Server Configuration — Can limit result rows but no column-level filtering for sensitive data
mediumVerified: 2025-11-09
compliance readiness

Compliance framework review

Evidence
Compliance Assessment — GDPR/HIPAA compliance depends on LLM provider and data handling configuration
mediumVerified: 2025-11-09
schema exposure

Metadata exposure analysis

Evidence
Schema Introspection — Database schema metadata shared with LLM for query generation
highVerified: 2025-11-09
👁️Trust & Transparency
+
documentation quality

Documentation completeness review

Evidence
MCP Postgres Docs — Clear documentation with setup instructions and security considerations
highVerified: 2025-11-09
query visibility

Query traceability assessment

Evidence
MCP Protocol Logging — All SQL queries logged and visible in MCP message stream
highVerified: 2025-11-09
open source code

Source code review

Evidence
GitHub Repository — Fully open source with MIT license
highVerified: 2025-11-09
security documentation

Security documentation review

Evidence
Security Guidelines — Provides security best practices but could be more comprehensive for database access
mediumVerified: 2025-11-09
⚙️Operational Excellence
+
ease of setup

Setup complexity assessment

Evidence
MCP Quickstart — Straightforward setup requiring connection string configuration
highVerified: 2025-11-09
performance

Performance benchmarking

Evidence
PostgreSQL Performance — Query performance depends on database configuration and optimization
highVerified: 2025-11-09
connection pooling

Connection management review

Evidence
Implementation Details — Supports connection pooling for efficient resource utilization
mediumVerified: 2025-11-09
error diagnostics

Error messaging assessment

Evidence
PostgreSQL Error Messages — Detailed error messages help diagnose issues
mediumVerified: 2025-11-09
community support

Community activity analysis

Evidence
MCP Community — Growing community support for database MCP servers
mediumVerified: 2025-11-09
Strengths
  • +Comprehensive PostgreSQL feature support including schema introspection
  • +Natural language to SQL query generation capabilities
  • +Excellent for data analysis and business intelligence workflows
  • +Full query visibility and logging for audit purposes
  • +Open source implementation with active development
  • +Supports connection pooling and performance optimization
Limitations
  • !High risk of exposing sensitive database content to LLM providers
  • !No built-in PII detection, redaction, or data anonymization
  • !AI can execute destructive operations (DELETE, DROP) if permissions allow
  • !Limited granular access control beyond database user permissions
  • !Query results with sensitive data sent to external APIs
  • !Compliance challenges for regulated industries (HIPAA, PCI-DSS, GDPR)
Metadata
license: MIT
supported platforms
0: All platforms with PostgreSQL client support
programming languages
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/modelcontextprotocol/servers-archived
github stars: 58700
database version: PostgreSQL 10+
connection method: Connection string with credentials
first release: 2024-11
maintained by: None (Archived)
status: Archived - No longer maintained
transport types
0: stdio
installation methods
0: npm

Use Case Ratings

code generation

Useful for generating database migration scripts and query code

customer support

Can help support teams query customer data, but privacy concerns exist

content creation

Limited applicability; mainly for content stored in databases

data analysis

Excellent for AI-powered data analysis, reporting, and insights generation

research assistant

Good for analyzing research datasets stored in PostgreSQL

legal compliance

High risk due to potential exposure of sensitive legal data to LLM providers

healthcare

Not recommended for PHI due to data exposure risks; HIPAA compliance challenges

financial analysis

Risky for sensitive financial data; requires strict access controls and data filtering

education

Good for analyzing student data and learning analytics

creative writing

Limited utility unless creative content is database-driven