SQLite MCP Server

Log Analysis with SQLite MCP Server

This project provides tools to create an SQLite database from compressed log files and interact with it using the Model Context Protocol (MCP) SQLite server.

Install instructions

python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt

Place log files in the folder as .gz files, then run:

python3 create_log_db.py 

MCP SQLite Server

To configure the MCP SQLite server in Cursor-

Cursor Settings
MCP
Add New MCP Server
Name SQLlite
Set the type to command
Put this in the command box

npx -y @smithery/cli@latest run mcp-server-sqlite-npx --config "{\"databasePath\":\"/path/to/thedatbase/logs.db\"}"

create_log_db.py: Script to extract and parse log files into an SQLite database
query_logs.py: Script to directly query the SQLite database
logs.db: SQLite database containing parsed log data

Database Structure

The database contains the following tables:

`logs` Table

id: Unique identifier for each log entry
timestamp: Timestamp of the log entry
thread: Thread that generated the log
level: Log level (INFO, WARN, ERROR, DEBUG)
module: Module that generated the log
message: Log message content
source_file: Source log file
raw_log: Raw log entry

`stack_traces` Table

id: Unique identifier for each stack trace
log_id: Reference to the log entry this stack trace belongs to
stack_trace: Full stack trace text

`parsing_errors` Table

id: Unique identifier for each parsing error
line: The line that couldn't be parsed
source_file: Source log file
error_message: Error message explaining why parsing failed
timestamp: When the parsing error occurred

You can query the database directly using the query_logs.py script:

This server cannot be installed

security - not tested

license - not found

quality - not tested

local-only server

The server can only run on the client's local machine because it depends on local resources.

Enables querying log data stored in SQLite databases through the Model Context Protocol, allowing natural language interactions with log analysis.

Related Resources

Reddit Discussion about this server

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