SQLite Explorer
数据与存储by wgong
Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view detailed schema metadata to understand structure quickly. Verify connectivity and readiness with a quick health check.
什么是 SQLite Explorer?
Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view detailed schema metadata to understand structure quickly. Verify connectivity and readiness with a quick health check.
README
Prerequisites
# Install dependencies
pip install -r requirements.txt
# Install FastMCP globally (if not already installed)
pip install fastmcp
COMMAND CHEATSHEET
# Run FastMCP directly for testing
SQLITE_DB_PATH=/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db fastmcp run sqlite_explorer.py
# Test with inspector (if available)
SQLITE_DB_PATH=/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db fastmcp inspect sqlite_explorer.py
# To install SQLite Explorer
SQLITE_DB_PATH=/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db fastmcp install sqlite_explorer.py --name "SQLite Explorer"
# To launch SQLite Explorer via a web-based testing interface. Run with `--transport sse` for HTTP-based communication
SQLITE_DB_PATH=/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db fastmcp dev sqlite_explorer.py
# To set up the MCP server with Claude Desktop
SQLITE_DB_PATH=/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db fastmcp claude-desktop add sqlite_explorer.py --name "SQLite Explorer"
# Need to define the SQLITE_DB_PATH variable before running smithery playground
SQLITE_DB_PATH=/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db smithery playground
After launching Smithery playground, we can now talk to the MCP server using this URL: https://smithery.ai/playground?mcp=https%3A%2F%2Fee09cd8f.ngrok.smithery.ai%2Fmcp
For VSCode with Cline
# Add this configuration to Cline MCP settings:
{
"sqlite-explorer": {
"command": "uv",
"args": [
"run",
"--with",
"fastmcp",
"--with",
"uvicorn",
"fastmcp",
"run",
"/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/sqlite_explorer.py"
],
"env": {
"SQLITE_DB_PATH": "/Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db"
}
}
}
Example output. MCP server provides four components. SQLite Explorer provides those tools.
Server Name: SQLite Explorer Generation: 2
Components Tools: 3 Prompts: 0 Resources: 0 Templates: 0
Environment FastMCP: 2.12.4 MCP: 1.15.0
This will open an interactive inspector where you can test the MCP tools:
- list_tables - to see what tables are in your database
- describe_table - to see the structure of a specific table
- read_query - to run SELECT queries on your data
Notes
Even though we're running the MCP locally, still have a web interface For locally deployed MCP server SQLite Explorer, this is the MCP server URL that we can access as a client: http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=e01acfa4461c1af5227669c2c0051e7cf9c280fb61a43a146a672463441f4c1b#tools In the future, once deployed, we'll have the same thing - HTTP or HTTPS, but instead of a local host, it'll be my server and the port. The rest will be something else. Local host is the server name, so the server is a local host. But if deployed somewhere, then it'll be a different host name. The port serves as a channel to talk to multiple MCP servers. HTTPS is a secure HTTP.
Sample Questions to Ask Your AI Assistant
Once the MCP server is connected, you can ask questions like:
- "What tables are in my database?"
- "Show me the structure of my financial data"
- "What are the first 10 rows from [table_name]?"
- "How many records are in each table?"
- "Show me all transactions over $1000"
- "What's the average amount in the transactions table?"
NOTE: The tables starting with SQLite are called system tables. We never created those tables.
Troubleshooting
# Check FastMCP version and available commands
fastmcp --help
fastmcp version
# Verify your database file exists
ls -la /Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db
# Test database directly with sqlite3
sqlite3 /Users/owner/claude-code/agentic-ai-learnings/hw3/sqlite-explorer-fastmcp-mcp-server/financial_data.db ".tables"
HW 3 Documentation
Step 1
Cloned this GitHub repository: https://github.com/hannesrudolph/sqlite-explorer-fastmcp-mcp-server
Step 2
Asked Claude Code: I was asked to evaluate the following deployment platforms: AWS, Vercel, Railway, and Smithery for my MCP server. I want the simplest and cheapest deployment. Which option should I select?
⏺ Based on your MCP server and requirements, I recommend Smithery.
Here's why:
Simplest: Smithery is specifically designed for MCP servers. It has the most straightforward deployment process for this exact use case.
Cheapest: Smithery offers a free tier for MCP server hosting, making it the most cost-effective option for your SQLite Explorer MCP server.
Other options comparison:
- AWS: Most complex setup, requires managing infrastructure, not cost-effective for simple MCP servers
- Vercel: Designed for web apps/APIs, not optimized for MCP servers, serverless model may not fit well
- Railway: Good platform but more expensive than Smithery's free tier, more general-purpose
For a read-only SQLite MCP server like yours, Smithery's MCP-specific infrastructure is the best match for "simplest and cheapest."
Step 3
Tested this locally via Cline. In VS Code, we configured the system settings to launch a web-based interface with the following JSON file. See URL: http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=a164e503687338cb23938baf05ae738ebe5cd0eaefa629e419cea7ef6ef51563#tools
Step 4
smithery playground URL : https://smithery.ai/playground?mcp=https%3A%2F%2F143c4151.ngrok.smithery.ai%2Fmcp
常见问题
SQLite Explorer 是什么?
Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view detailed schema metadata to understand structure quickly. Verify connectivity and readiness with a quick health check.
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