databasesdeveloper-tools

pg-aiguide

timescale

by timescale

pg-aiguide — Version-aware PostgreSQL docs and best practices tailored for AI coding assistants. Improve queries, migrat

Version-aware PostgreSQL documentation and best practices for AI coding assistants

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Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Public MCP server — no setup requiredVersion-aware PostgreSQL documentationAI-optimized skills and patterns

best for

  • / AI coding assistants writing PostgreSQL code
  • / Developers needing modern PostgreSQL best practices
  • / Teams working with TimescaleDB

capabilities

  • / Search PostgreSQL documentation semantically
  • / Access TimescaleDB and Tiger Cloud documentation
  • / Retrieve PostgreSQL best practices and design patterns
  • / Get version-aware PostgreSQL guidance

what it does

Provides AI coding assistants with semantic search across PostgreSQL documentation and curated best practices to generate better, more modern PostgreSQL code.

about

pg-aiguide is an official MCP server published by timescale that provides AI assistants with tools and capabilities via the Model Context Protocol. pg-aiguide — Version-aware PostgreSQL docs and best practices tailored for AI coding assistants. Improve queries, migrat It is categorized under databases, developer tools. This server exposes 3 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install pg-aiguide in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server supports remote connections over HTTP, so no local installation is required.

license

Apache-2.0

pg-aiguide is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

pg-aiguide

AI-optimized PostgreSQL expertise for coding assistants

pg-aiguide helps AI coding tools write dramatically better PostgreSQL code. It provides:

  • Semantic search across the official PostgreSQL manual (version-aware)
  • AI-optimized “skills” — curated, opinionated Postgres best practices used automatically by AI agents
  • Extension ecosystem docs, starting with TimescaleDB, with more coming soon

Use it either as:

  • a public MCP server that can be used with any AI coding agent, or
  • a Claude Code plugin optimized for use with Claude's native skill support.

⭐ Why pg-aiguide?

AI coding tools often generate Postgres code that is:

  • outdated
  • missing constraints and indexes
  • unaware of modern PG features
  • inconsistent with real-world best practices

pg-aiguide fixes that by giving AI agents deep, versioned PostgreSQL knowledge and proven patterns.

See the difference

https://github.com/user-attachments/assets/5a426381-09b5-4635-9050-f55422253a3d

<details> <summary>Video Transcript </summary>

Prompt given to Claude Code:

Please describe the schema you would create for an e-commerce website two times, first with the tiger mcp server disabled, then with the tiger mcp server enabled. For each time, write the schema to its own file in the current working directory. Then compare the two files and let me know which approach generated the better schema, using both qualitative and quantitative reasons. For this example, only use standard Postgres.

Result (summarized):

  • 4× more constraints
  • 55% more indexes (including partial/expression indexes)
  • PG17-recommended patterns
  • Modern features (GENERATED ALWAYS AS IDENTITY, NULLS NOT DISTINCT)
  • Cleaner naming & documentation

Conclusion: pg-aiguide produces more robust, performant, maintainable schemas.

</details>

🚀 Quickstart

pg-aiguide is available as a public MCP server:

https://mcp.tigerdata.com/docs

<details> <summary>Manual MCP configuration using JSON</summary>
{
  "mcpServers": {
    "pg-aiguide": {
      "url": "https://mcp.tigerdata.com/docs"
    }
  }
}
</details>

Or it can be used as a Claude Code Plugin:

claude plugin marketplace add timescale/pg-aiguide
claude plugin install pg@aiguide

Install by environment

One-click installs

Install in Cursor Install in VS Code Install in VS Code Insiders Install in Visual Studio Install in Goose Add MCP Server pg-aiguide to LM Studio

<details> <summary>Claude Code</summary>

This repo serves as a claude code marketplace plugin. To install, run:

claude plugin marketplace add timescale/pg-aiguide
claude plugin install pg@aiguide

This plugin uses the skills available in the skills directory as well as our publicly available MCP server endpoint hosted by TigerData for searching PostgreSQL documentation.

</details> <details> <summary> Codex </summary>

Run the following to add the MCP server to codex:

codex mcp add --url "https://mcp.tigerdata.com/docs" pg-aiguide
</details> <details> <summary> Cursor </summary>

One-click install:

Install MCP Server

Or add the following to .cursor/mcp.json

{
  "mcpServers": {
    "pg-aiguide": {
      "url": "https://mcp.tigerdata.com/docs"
    }
  }
}
</details> <details> <summary> Gemini CLI </summary>

Run the following to add the MCP server to Gemini CLI:

gemini mcp add -s user pg-aiguide "https://mcp.tigerdata.com/docs" -t http
</details> <details> <summary> Visual Studio </summary>

Click the button to install:

Install in Visual Studio

</details> <details> <summary> VS Code </summary>

Click the button to install:

Install in VS Code

Alternatively, run the following to add the MCP server to VS Code:

code --add-mcp '{"name":"pg-aiguide","type":"http","url":"https://mcp.tigerdata.com/docs"}'
</details> <details> <summary> VS Code Insiders </summary>

Click the button to install:

Install in VS Code Insiders

Alternatively, run the following to add the MCP server to VS Code Insiders:

code-insiders --add-mcp '{"name":"pg-aiguide","type":"http","url":"https://mcp.tigerdata.com/docs"}'
</details> <details> <summary> Windsurf </summary>

Add the following to ~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "pg-aiguide": {
      "serverUrl": "https://mcp.tigerdata.com/docs"
    }
  }
}
</details>

💡 Your First Prompt

Once installed, pg-aiguide can answer Postgres questions or design schemas.

Simple schema example prompt

Create a Postgres table schema for storing usernames and unique email addresses.

Complex schema example prompt

You are a senior software engineer. You are given a task to generate a Postgres schema for an IoT device company. The devices collect environmental data on a factory floor. The data includes temperature, humidity, pressure, as the main data points as well as other measurements that vary from device to device. Each device has a unique id and a human-readable name. We want to record the time the data was collected as well. Analysis for recent data includes finding outliers and anomalies based on measurements, as well as analyzing the data of particular devices for ad-hoc analysis. Historical data analysis includes analyzing the history of data for one device or getting statistics for all devices over long periods of time.

Features

Documentation Search (MCP Tools)

  • search_docs Unified search tool supporting semantic (vector similarity) and keyword (BM25) search across multiple documentation sources:
    • postgres - Official PostgreSQL manual, scoped by version
    • tiger - Tiger Data's documentation (TimescaleDB and ecosystem)
    • postgis - PostGIS spatial extension documentation

Skills (AI-Optimized Best Practices)

  • view_skill
    Exposes curated, opinionated PostgreSQL best-practice skills used automatically by AI coding assistants.

    These skills provide guidance on:

    • Schema design
    • Indexing strategies
    • Data types
    • Data integrity and constraints
    • Naming conventions
    • Performance tuning
    • Modern PostgreSQL features

🔌 Ecosystem Documentation

Supported today:

  • TimescaleDB (docs + skills)
  • PostGIS (docs)

Coming soon:

  • pgvector

We welcome contributions for additional extensions and tools.

🛠 Development

See DEVELOPMENT.md for:

  • running the MCP server locally
  • adding new skills
  • adding new docs

🤝 Contributing

We welcome:

  • new Postgres best-practice skills
  • additional documentation corpora
  • search quality improvements
  • bug reports and feature ideas

📄 License

Apache 2.0

FAQ

What is the pg-aiguide MCP server?
pg-aiguide is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for pg-aiguide?
This profile displays 32 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.4 out of 5—verify behavior in your own environment before production use.

Use Cases

Direct Database Queries from AI

Enable Claude to query your database directly using natural language

Example

Ask 'Show me top 10 customers by revenue this month' and get SQL results instantly

Eliminate manual SQL writing for ad-hoc queries, get insights 10x faster

Data Analysis & Reporting

Generate complex reports and analytics without leaving conversation

Example

Analyze sales trends, cohort retention, user behavior patterns conversationally

Democratize data access—non-technical team members can query databases

Schema Exploration

Understand database structure, relationships, and data models

Example

'Explain the user_orders table schema and its relationships'

Onboard engineers faster, explore unfamiliar databases efficiently

Data Validation & Quality Checks

Run data quality queries to catch anomalies and inconsistencies

Example

Find duplicate records, missing values, orphaned foreign keys automatically

Maintain data integrity with less manual SQL work

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor with MCP support
  • Database credentials (read-only recommended for safety)
  • Network access from Claude client to database
  • Understanding of database security and access control

Time Estimate

15-30 minutes including configuration and testing

Installation Steps

  1. 1.Install MCP server: npm install -g @modelcontextprotocol/server-[name]
  2. 2.Configure database connection in Claude Desktop config (~/.claude/mcp.json)
  3. 3.Provide connection string: host, port, database, username, password
  4. 4.Restart Claude Desktop to load MCP server
  5. 5.Test connection: 'List all tables in database'
  6. 6.Run simple query: 'Show me 5 rows from users table'
  7. 7.Verify results and permissions are correct
  8. 8.Document query patterns for team use

Troubleshooting

  • Connection refused: Check database is running and network accessible
  • Authentication failed: Verify credentials, check user permissions
  • Claude can't see tables: Grant appropriate read permissions to database user
  • Slow queries: Add indexes, limit result set size, use read replicas
  • MCP server not loading: Check config syntax, restart Claude Desktop

Best Practices

✓ Do

  • +Use read-only database credentials to prevent accidental writes
  • +Connect to read replica, not production primary database
  • +Set query timeout limits to prevent long-running queries
  • +Document database schema and common queries for AI context
  • +Monitor query performance and optimize slow queries
  • +Use connection pooling for better performance
  • +Test with non-production data first

✗ Don't

  • Don't use production write credentials—risk of data corruption
  • Don't query production database during peak traffic hours
  • Don't expose sensitive PII without proper access controls
  • Don't skip query result validation—AI can misinterpret schema
  • Don't allow unlimited result set sizes—set LIMIT clauses
  • Don't share database credentials in plain text config files

💡 Pro Tips

  • Create database views for common queries to simplify AI access
  • Add schema comments/descriptions so AI understands column meanings
  • Use semantic table/column names ('customer_lifetime_value' not 'clv')
  • Set up query logging to audit what Claude is querying
  • Create saved query templates for recurring analysis
  • Combine with data visualization tools for better insights

Technical Details

Architecture

MCP server acts as bridge between Claude and database, translating natural language to SQL queries and returning results in structured format.

Protocols

  • Model Context Protocol (MCP)
  • Database-specific protocols (PostgreSQL, MySQL, MongoDB)

Compatibility

  • PostgreSQL
  • MySQL
  • SQLite
  • MongoDB
  • Redis

When to Use This

✓ Use When

Use for ad-hoc data queries, exploratory analysis, report generation, schema exploration, and democratizing data access. Best for read-heavy analytics workloads.

✗ Avoid When

Avoid for production write operations, mission-critical transactions, real-time OLTP workloads, or when database contains sensitive PII without proper access controls. Use read replicas, not primary.

Integration

  • Read replica connection for analytics queries
  • Database view layer to abstract complex joins
  • Query result caching for repeated questions
  • Audit logging of all AI-generated queries

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.432 reviews
  • Shikha Mishra· Dec 16, 2024

    pg-aiguide reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Rahul Santra· Nov 7, 2024

    I recommend pg-aiguide for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Pratham Ware· Oct 26, 2024

    Strong directory entry: pg-aiguide surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Min Park· Sep 17, 2024

    pg-aiguide reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Lucas Martin· Sep 9, 2024

    pg-aiguide has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Isabella White· Aug 28, 2024

    According to our notes, pg-aiguide benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Camila Wang· Aug 8, 2024

    Useful MCP listing: pg-aiguide is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Amina Wang· Jul 27, 2024

    Strong directory entry: pg-aiguide surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Lucas Abebe· Jul 27, 2024

    pg-aiguide is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Yash Thakker· Jul 19, 2024

    pg-aiguide is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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