Server data from the Official MCP Registry
Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view det…
Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view det…
Remote endpoints: streamable-http: https://server.smithery.ai/@wgong/sqlite-mcp-server/mcp
Valid MCP server (0 strong, 5 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
5 files analyzed · No issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
# Install dependencies
pip install -r requirements.txt
# Install FastMCP globally (if not already installed)
pip install fastmcp
# 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
# 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"
}
}
}
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:
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.
Once the MCP server is connected, you can ask questions like:
NOTE: The tables starting with SQLite are called system tables. We never created those tables.
# 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"
Cloned this GitHub repository: https://github.com/hannesrudolph/sqlite-explorer-fastmcp-mcp-server
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:
For a read-only SQLite MCP server like yours, Smithery's MCP-specific infrastructure is the best match for "simplest and cheapest."
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
smithery playground URL : https://smithery.ai/playground?mcp=https%3A%2F%2F143c4151.ngrok.smithery.ai%2Fmcp
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