mcp-forge
Exposes SQLite database tools for listing tables, describing table schemas, and executing read-only SQL queries.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-forge turn ./my_database.db into an MCP server and give me the config"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
β‘ mcp-forge (mforge)
Instant Model Context Protocol (MCP) server generator. Connect SQLite databases and folders to Claude Desktop and Cursor in seconds.
Model Context Protocol (MCP) by Anthropic is the new open standard for connecting AI assistants to data sources and tools.
mcp-forge allows developers to turn any SQLite database or local directory into a production-ready, zero-dependency MCP server with one CLI command.
π Support & Sponsor
If mcp-forge helped you connect data to Claude or Cursor, consider buying me a coffee:
π buymeacoffee.com/carlosdevkadu
Related MCP server: mcp-sequel
β‘ Highlights
ποΈ Instant SQLite Server: Exposes
list_tables,describe_table, andexecute_query(with built-in read-only safety).π Instant Filesystem Server: Exposes
list_directory,read_file, andsearch_textacross any target directory.βοΈ Auto Claude Config: Generates ready-to-paste JSON blocks for your
claude_desktop_config.json.π¦ Zero External Dependencies: Pure Python JSON-RPC 2.0 stdio implementation.
π Quick Start
Installation
pip install .1. Connect a SQLite Database to Claude Desktop
Generate the configuration snippet:
mforge config sqlite ./my_database.dbOutput:
{
"mcpServers": {
"mcp-my_database": {
"command": "python",
"args": ["-m", "mcp_forge.cli", "sqlite", "C:/path/to/my_database.db"]
}
}
}Paste this into your claude_desktop_config.json and restart Claude!
2. Connect a Project Folder to Claude Desktop
mforge config folder ./my-project-docsπ License
Distributed under the MIT License.
Available Tools
3 toolsdescribe_tableA
Describes the schema and column definitions of a specific table.
Inputs: table_name (required).
execute_queryB
Executes a SQL SELECT query on the SQLite database and returns rows.
Inputs: query (required).
list_tablesA
Lists all user tables in the SQLite database.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelogβ¦
TDQS
Scored across 3 tools
Each tool targets a clearly distinct layer: enumerating tables, inspecting one table's schema, and running row-returning queries. An agent can trivially pick the right one from names alone. No overlap between describe_table (metadata) and execute_query (data).
All three follow the verb_noun snake_case pattern (list_tables, describe_table, execute_query), which is highly predictable. The only minor inconsistency is singular vs. plural nouns (tables vs. table), though that actually reflects list-vs-single semantics.
Three tools is on the thin edge for a database server; a listing, a schema descriptor, and one query executor cover the basics but leave little room for inspection workflows. It's borderline rather than wrong-sized, since the surface is deliberately minimal.
Read-only exploration is covered, but execute_query is explicitly limited to SELECT, so there is no way to create tables, insert, update, or delete β an obvious gap for a database tool. Agents hitting a need to mutate data or run DDL will dead-end, though exploration tasks are fully served.
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