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  1. Home
  2. 🗄️ Databases
  3. Afgong Sqlite Mcp Server
Afgong Sqlite Mcp Server logo
Health: ActiveRecent health check succeeded.Last checked 8/10/2026, 11:03:01 PM

Afgong Sqlite Mcp Server

Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time — check back soon.
View Repository

Explore your Messages SQLite database to browse tables and inspect schemas with ease. Run flexible…

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Install Config Generator

Choose your client
claude_desktop_config.json
{
  "mcpServers": {
    "afgong-sqlite-mcp-server": {
      "command": "uvx",
      "args": [
        "fastmcp"
      ]
    }
  }
}

💡 Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)

Install Directory Badge Claim listing Alternatives🗄️ More in Databases

Documentation Overview

Prerequisites

bash
# Install dependencies
pip install -r requirements.txt

# Install FastMCP globally (if not already installed)
pip install fastmcp

COMMAND CHEATSHEET

bash
# 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

bash
# 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

bash
# 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

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Frequently Asked Questions about Afgong Sqlite Mcp Server

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "afgong-sqlite-mcp-server": { "command": "npx", "args": ["-y", "afgong-sqlite-mcp-server"] } }

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Technical Specs & Signals

Category🗄️Databases
More technical detailsExpand ▾
TransportSTDIO
RuntimePython
Views0
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Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars0
GitHub Star CountTotal stargazers on GitHub representing community popularity (0 stars).
Last commit10mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Oct 2, 2025
35Quality signal: Fair · 35/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools16/30
Adoption & activity0/15
Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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