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SQLite MCP Server

by isaacgounton
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JavaScript
Hybrid

SQLite MCP 服务器

通过标准化接口提供 SQLite 数据库操作的模型上下文协议 (MCP) 服务器。

特征

  • 内存 SQLite 数据库（可配置为基于文件的存储）

  • SQL 操作（SELECT、INSERT、UPDATE、DELETE）

  • 表管理（CREATE、LIST、DESCRIBE）

  • 业务洞察备忘录跟踪

  • Docker 支持，轻松部署

Related MCP server: SQLite MCP Server

开发与部署

本地开发

# Install dependencies and build
npm install
npm start

Docker 部署

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

Nixpacks部署

该应用程序可以使用 Nixpacks 与 Railway、Coolify 或 Render 等平台轻松部署：

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

由于该项目包含 Dockerfile，因此不需要额外的配置。

可用工具

  1. read_query ：执行 SELECT 查询

  2. write_query ：执行 INSERT、UPDATE 或 DELETE 查询

  3. create_table ：创建新表

  4. list_tables ：列出数据库中的所有表

  5. describe_table ：查看表的架构信息

  6. append_insight ：将业务见解添加到备忘录中

远程服务器连接

要在 n8n 中使用 SSE 进行连接：

  1. 添加 MCP 客户端节点

  2. 配置 SSE 连接：

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

    • 消息发布端点： http://localhost:3000/messages

    • 无需额外的标题

示例用法

// 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'
});

环境变量

默认无需配置。如果使用文件存储，请修改src/index.ts中的数据库路径。

贡献

  1. 分叉存储库

  2. 创建你的功能分支（ git checkout -b feature/amazing-feature ）

  3. 提交您的更改（ git commit -m 'Add some amazing feature' ）

  4. 推送到分支（ git push origin feature/amazing-feature ）

  5. 打开拉取请求

执照

国际学习中心

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
Install Server
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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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