Riohari07/ai-assisted-insights-agent

View on GitHub by @Riohari07

🤖 Translate natural language questions into clear, accurate data insights with this MCP-compatible AI agent for effective decision-making.

What's novel

🤖 Translate natural language questions into clear, accurate data insights with this MCP-compatible AI agent for effective decision-making.

Code Analysis

12 files read · 4 rounds

An MCP server that uses simple keyword matching against 4 hardcoded metrics to generate templated SQL queries and return simulated (fake) numeric results with canned data quality reports.

Strengths

The MCP tool interface is well-structured with clear docstrings, and the test suite covers the main tool functions with reasonable assertions. The CLI wrapper and SQLite history module are cleanly written even though they're disconnected from the server.

Weaknesses

All data is hardcoded and all query results are simulated — there is no real database connection, no real NLP, and no actual AI. The README describes a downloadable desktop app with a GUI that doesn't exist, and config.py/history.py are dead code never imported by the server.

Score Breakdown

Innovation

3 (25%)

Craft

55 (35%)

Traction

11 (15%)

Scope

53 (25%)

Signal breakdown

Innovation

Not Fork+1

Code Novelty+0

Concept Novelty+0

Craft

Ci-3

Tests+5

Polish+1

Releases-2

Has License+5

Code Quality+15

Readme Quality+15

Recent Activity+7

Structure Quality+5

Commit Consistency+2

Has Dependency Mgmt+5

Traction

Forks+0

Stars+6

Hn Points+0

Watchers+3

Early Traction+0

Devto Reactions+0

Community Contribs+2

Scope

Commits+5

Languages+5

Subsystems+13

Bloat Penalty+0

Completeness+7

Contributors+7

Authored Files+12

Readme Code Match+3

Architecture Depth+5

Implementation Depth+8

Evidence

Commits

Contributors

Files

Active weeks

TestsCI/CDREADMELicenseContributing

Repository

Language

Python

Stars

Forks

License

MIT