
Afgong Sqlite Mcp Server
- Updated October 2, 2025
- afgong/sqlite-mcp-server
ai.smithery/afgong-sqlite-mcp-server is an MCP server that lets agents explore and query a local Messages SQLite database via schema-aware tools.
About
ai.smithery/afgong-sqlite-mcp-server is a Smithery-hosted MCP server that lets coding agents interact with a Messages-style SQLite database: discover tables, read schema metadata, and execute exploratory queries without opening DB Browser manually. Developers automating personal workflows, prototyping iMessage-adjacent tools, or learning how MCP wraps SQLite will register this during the build phase as an integration layer. The implementation is rooted in a FastMCP SQLite explorer pattern from GitHub, exposed remotely so Claude Code, Cursor, or Codex can call tools over streamable HTTP with a Smithery API key. Treat the database path and host permissions as your responsibility—the server amplifies agent access to data you already have locally. It is inappropriate for production multi-tenant messaging products without hardening, migration strategy, and privacy review; it shines for experimentation, one-off exports, and schema reconnaissance before you write proper ETL or app code.
- Explore Messages SQLite: browse tables and inspect schemas
- Run flexible queries through MCP tools (FastMCP-based server)
- Smithery streamable HTTP remote with Bearer authentication (v1.16.0)
- Source repo afgong/sqlite-mcp-server (sqlite-explorer-fastmcp-mcp-server subfolder)
- Local-database focus—not a hosted warehouse or ORM generator
Afgong Sqlite Mcp Server by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
claude mcp add --transport http afgong-sqlite-mcp-server https://server.smithery.ai/@afgong/sqlite-mcp-server/mcp --header "Authorization: Bearer YOUR_TOKEN"Add your badge
Show developers this MCP server is listed on Skillselion. Paste this into your README.
| Transport | HTTP |
|---|---|
| Auth | Required |
| Last updated | October 2, 2025 |
| Repository | afgong/sqlite-mcp-server ↗ |
What it does
Let your agent browse schemas, list tables, and run flexible SQL against your local Apple Messages SQLite database for debugging, exports, or personal automation experiments.
Who is it for?
Best when you're on macOS experimenting with message archives, personal analytics, or SQLite-backed agent tooling.
Skip if: Production customer inboxes, team-wide CRM, or regulated PHI workflows without explicit access controls and legal review.
What you get
After MCP registration, your agent can list tables, inspect schemas, and run flexible queries against the configured SQLite file from the chat thread.
- Table listings and schema descriptions from the SQLite file
- Query results returned into the agent session for analysis or codegen
- Clearer picture of columns and relationships before you ship export scripts
By the numbers
- Server version 1.16.0 in published server metadata
- GitHub repository afgong/sqlite-mcp-server with sqlite-explorer-fastmcp-mcp-server subfolder
- Smithery remote type streamable-http
README.md
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
Recommended MCP Servers
How it compares
Local SQLite explorer MCP, not a hosted Postgres admin or a data-pipeline ETL skill.
FAQ
Who is ai.smithery/afgong-sqlite-mcp-server for?
Developers who want their AI agent to browse and query a Messages SQLite database for personal projects, debugging, or prototyping integrations.
When should I use ai.smithery/afgong-sqlite-mcp-server?
Use it during build when you need schema discovery or exploratory SQL against a local SQLite Messages store before writing app or export code.
How do I add ai.smithery/afgong-sqlite-mcp-server to my agent?
Configure the Smithery remote for @afgong/sqlite-mcp-server with Bearer smithery_api_key in your MCP client and ensure the agent runtime can reach the database path your deployment expects.