MCP server
SQLite MCP server
A community MCP server for SQLite files that lets AI list tables, read and change records and run SQL on a local database.
- Community server
- Databases
At a glance
- Maintained by
- eQuill Labs (jparkerweb, community)
- Tools exposed
- 8 listed below
- Reviewed
- September 24, 2026
Why it matters
What it does and why it matters
SQLite is the database inside many desktop apps, mobile apps, prototypes and small tools. Its data lives in a single file. An SQLite MCP server lets an AI assistant open that file, understand its tables and answer questions or make changes, which is handy for prototypes, local tools and data clean-up.
The original MCP reference server for SQLite was archived in May 2025. The option listed here is a community server by eQuill Labs, with tools for reading, creating, updating and deleting records, plus raw SQL.
It has full read and write access, including deletes, and we found no read-only switch in its documentation. That makes it best suited to copies of data, prototypes and local analysis rather than live systems. Always work on a copy of the file when the data matters.
Use cases
Best business use cases
Prototype data
App data inspection
Quick analysis
Data clean-up
Learning SQL
Tools
Available tools
Tool names as published by the maintainer at review time. Versions change, so check the repository for the current list.
Read and write: Full read and write, including deletes and raw SQL; no read-only switch documented.
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db_infoGets details about the connected database.
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list_tablesLists all tables in the database.
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get_table_schemaShows a table's columns and schema.
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create_recordInserts a new record into a table.
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read_recordsReads records with optional filters.
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update_recordsUpdates records that match conditions.
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delete_recordsDeletes records that match conditions.
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queryRuns a custom SQL query.
Workflows
Example workflows
Analyze an exported dataset
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1
Copy the export into a new SQLite file.
-
2
Point the server at the copy.
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3
Ask the assistant to describe the tables.
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4
Ask questions and get answers with the SQL shown.
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5
Save useful queries for later.
Clean a prototype database
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1
Make a backup of the file.
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2
Ask the assistant to find duplicate or empty records.
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3
Review the list it returns.
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4
Approve the updates or deletes.
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5
Compare record counts before and after.
Prompts
Example prompts
“Describe every table in this database and how they relate.”
“Find customers with no email address and list them.”
“Show the SQL you would use to merge duplicate products, but do not run it yet.”
Setup
Installation and configuration
Examples for Claude Desktop and Claude Code. Replace the placeholder values with your own keys, and store secrets outside version control.
Claude Desktop: claude_desktop_config.json
{
"mcpServers": {
"MCP SQLite Server": {
"command": "npx",
"args": [
"-y",
"mcp-sqlite",
"<path-to-your-sqlite-database.db>"
]
}
}
}Claude Code: terminal
claude mcp add sqlite -- npx -y mcp-sqlite /path/to/your-database.db- Local server: stdio. npm: mcp-sqlite (takes the database file path as an argument).
- Needs: None. Needs a local path to the SQLite database file..
Security
Security considerations
-
Work on copies
The server can delete data. Use a copy of the file for anything important.
-
Limit the path
Point it only at the file it needs.
-
Review changes
Ask the assistant to show SQL before running changes.
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Community code
Review the code and pin the version before use.
Related servers
Servers that pair well with it
PostgreSQL
Lets AI assistants explore a PostgreSQL database, run SQL in a restricted read-only mode and check query performance and database health.
MySQL
A community MCP server that lets AI run SQL against MySQL, read-only by default, with insert, update and delete each switched on separately.
Filesystem
The MCP project's Filesystem reference server lets AI read, write, edit, move and search files, only inside folders you allow.
Keep exploring
Solutions and services that use it
Related services
View all related services- MCP integration Connect AI assistants to your CRM, files, databases and tools through Model Context Protocol servers, with safe permissions.
- Database design Data models that stay fast and correct as your business grows, with backups and access rules in place.
- Web applications Custom browser-based software for the work your team does every day, from booking tools to operations systems.
- Dashboards and reporting Dashboards that pull numbers from the systems you already use and show what matters without a spreadsheet.
- Multi-tenant architecture One product serving many customer accounts, with each account's data kept separate and secure.
- Product scaling Keep a growing product fast and stable as users, data and features increase.
Solutions
View all solutions- Automated reporting Reports that build themselves from your systems on schedule, with a plain-language summary of what changed.
- Knowledge assistant (RAG) Ask a question in plain words and get an answer from your own documents, with links to the sources.
- Forecasting dashboards Forecast demand from your sales history and seasonality, and flag items to reorder before they run out.
- Payroll automation Turn pay rules, attendance and leave into tested software so the monthly run becomes a review and payslips go out in one batch.
- AI automation and integrations Connect the tools you already use so data moves once, correctly, and AI reads the parts that arrive as text or documents.
Industries
View all industriesCase studies
View all case studiesGuides and articles
View all guides and articles- How to connect AI to your database safely Let staff ask questions of your data in plain English without risking production systems or sensitive records.
- PostgreSQL vs MySQL The two most popular open-source databases compared for business applications.
- How to automate reporting with AI and MCP Build reports that assemble themselves from your systems through MCP, with a written summary people can trust.
- How to set up automated reporting Replace manual weekly and monthly reports with dashboards and summaries that update themselves.
AI models
View all ai models- text-embedding-3-large OpenAI's most capable embedding model for search and retrieval, with 3,072-dimension vectors and support for English and other languages.
- text-embedding-3-small OpenAI's efficient, lowest-cost embedding model, with 1,536-dimension vectors for search, retrieval and similarity at scale.
- Cohere Embed v4 Cohere's multimodal embedding model for enterprise search, embedding text, images and mixed documents, with flexible vector sizes and long inputs.
- Voyage 4 Voyage AI's current embedding series, now part of MongoDB, with large, standard and lite models that share one embedding space.
- Embeddings Models that turn text into vectors for search, retrieval, clustering and recommendations.
Glossary terms
View all glossary terms- Database A database is an organized store of data that software can search, update and keep consistent, such as customers, orders or bookings.
- MVP An MVP, or minimum viable product, is the smallest version of a product that real users can use and pay for, built to learn quickly what works.
- Vector database A vector database stores embeddings, lists of numbers that represent meaning, and quickly finds the ones most similar to a query.
- Backend The backend is the part of an application that runs on servers, storing data, applying business rules and serving the frontend through APIs.
- Embeddings Embeddings are lists of numbers that represent the meaning of text or images, so software can find items that are similar in meaning.
- MCP server An MCP server is a program or hosted service that exposes a system's data and actions as tools that AI assistants can use through the Model Context Protocol.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
No. It was archived in May 2025. The server listed here is a community alternative.
We found no read-only switch documented. Use a copy of the file when the data matters.
No. It needs only the path to the database file.