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isaacgounton

SQLite MCP Server

by isaacgounton
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SQLite MCP 서버

표준화된 인터페이스를 통해 SQLite 데이터베이스 작업을 제공하는 MCP(Model Context Protocol) 서버입니다.

특징

  • 메모리 내 SQLite 데이터베이스(파일 기반 스토리지에 맞게 구성 가능)

  • SQL 작업(SELECT, INSERT, UPDATE, DELETE)

  • 테이블 관리(CREATE, LIST, DESCRIBE)

  • 비즈니스 인사이트 메모 추적

  • 간편한 배포를 위한 Docker 지원

Related MCP server: SQLite MCP Server

개발 및 배포

지역 개발

지엑스피1

도커 배포

# Build and run with Docker
docker build -t sqlite-mcp-server .
docker run -d --name sqlite-mcp sqlite-mcp-server

Nixpacks 배포

Nixpacks를 사용하면 Railway, Coolify 또는 Render와 같은 플랫폼을 통해 애플리케이션을 쉽게 배포할 수 있습니다.

# Deploy with Nixpacks
nixpacks build . --name sqlite-mcp-server

프로젝트에 Dockerfile이 포함되어 있으므로 추가 구성이 필요하지 않습니다.

사용 가능한 도구

  1. read_query : SELECT 쿼리 실행

  2. write_query : INSERT, UPDATE 또는 DELETE 쿼리를 실행합니다.

  3. create_table : 새로운 테이블 생성

  4. list_tables : 데이터베이스의 모든 테이블을 나열합니다

  5. describe_table : 테이블에 대한 스키마 정보 보기

  6. append_insight : 메모에 비즈니스 통찰력 추가

원격 서버 연결

n8n에서 SSE를 사용하여 연결하려면:

  1. MCP 클라이언트 노드 추가

  2. SSE 연결 구성:

    • SSE URL: http://localhost:3000/sse

    • 메시지 게시 엔드포인트: http://localhost:3000/messages

    • 추가 헤더가 필요하지 않습니다

사용 예

// Create a table
await callTool('create_table', {
  query: 'CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)'
});

// Insert data
await callTool('write_query', {
  query: 'INSERT INTO users (name) VALUES ("John Doe")'
});

// Query data
const result = await callTool('read_query', {
  query: 'SELECT * FROM users'
});

환경 변수

기본적으로 필요하지 않습니다. 파일 기반 저장소를 사용하는 경우 src/index.ts 에서 데이터베이스 경로를 수정하세요.

기여하다

  1. 저장소를 포크하세요

  2. 기능 브랜치를 생성합니다( git checkout -b feature/amazing-feature )

  3. 변경 사항을 커밋하세요( git commit -m 'Add some amazing feature' )

  4. 브랜치에 푸시( git push origin feature/amazing-feature )

  5. 풀 리퀘스트 열기

특허

아이에스씨

Available Tools

1 tool
create_tableB

Create a new table in the database with a full CREATE TABLE SQL statement.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesCREATE TABLE SQL statement

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention side effects (e.g., if table exists), permission requirements, or that it modifies state, which is critical for a write operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence with no wasted words, though minor expansion for behavioral details would improve it without harming conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool with no output schema, the description covers the essential purpose but lacks details on error handling, permission requirements, or SQL dialect support.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes the 'query' parameter fully. The description adds the word 'full', implying a complete statement, but no additional meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'create', the resource 'table', and specifies it uses a full CREATE TABLE SQL statement, effectively distinguishing it from sibling tools like drop_table or list_tables.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for creating a table but provides no explicit guidance on when to use this tool versus alternatives like write_query, nor when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 6 tool updatesv1.1.0
    • Removedappend_insight
    • Removeddescribe_table
    • Removeddrop_table
    • Removedlist_tables
    • Removedread_query
    • Removedwrite_query
  2. 7 tool updates
    • Addedappend_insight
    • Addedcreate_table
    • Addeddescribe_table
    • Addeddrop_table
    • Addedlist_tables
    • Addedread_query
    • Addedwrite_query
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TDQS

B3.4/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion between tools. The single tool's purpose is clearly distinct by default.

Naming Consistency5/5

With a single tool, naming consistency is trivially maintained. The name 'create_table' follows a clear verb_noun pattern.

Tool Count2/5

A single tool for a SQLite server is far too few for the apparent scope. Typical database operations are missing, making the tool set feel extremely thin.

Completeness2/5

The server only supports table creation, lacking essential operations like querying, inserting, updating, deleting, or dropping tables. This represents significant gaps for any database interaction.

Maintenance

ActivitySlowing
ResponsivenessSlow

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

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  • SQLite MCP Server

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