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a-i-m-a-n/mcp

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CSV Insight & Cleaner is a minimalistic Model Context Protocol (MCP) server that lets an AI assistant — without loading raw file paths or guessing at missing data.

개요

CSV Insight & Cleaner is a minimalistic Model Context Protocol (MCP) server that lets an AI assistant — without loading raw file paths or guessing at missing data. Built with the official Python MCP SDK (FastMCP) and pandas, in a small, readable, single-file codebase. - ⚡ — one server.py, under 150 lines. - 🎯 : Tools (inspect/summarize/clean/preview/report/export), Resources (live dataset + report snapshots), Prompts (analysis & cleaning workflows). - 🧠 — Python/pandas computes the facts (row counts, duplicates, missing values); the AI client turns those facts into natural language. The server never invents or silently guesses data. - 🔒 — missing values are reported, never auto-filled. Only deterministic, reversible cleanup (duplicates, empty rows, whitespace, column names) is automated. - 🌐 — tools accept raw CSV , not local file paths, so the same server works locally and once deployed publicly (e.g. on Glama), where it has no access to your filesystem. 1.

README

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CSV Insight & Cleaner MCP 📊🧹

CSV Insight & Cleaner is a minimalistic Model Context Protocol (MCP) server that lets an AI assistant understand, quality-check, and clean CSV datasets — without loading raw file paths or guessing at missing data.

Built with the official Python MCP SDK (FastMCP) and pandas, in a small, readable, single-file codebase.

🌟 Key Highlights

  • ⚡ Minimal & Zero-Bloat — one server.py, under 150 lines.
  • 🎯 All 3 MCP Primitives: Tools (inspect/summarize/clean/preview/report/export), Resources (live dataset + report snapshots), Prompts (analysis & cleaning workflows).
  • 🧠 Facts vs. Explanation split — Python/pandas computes the facts (row counts, duplicates, missing values); the AI client turns those facts into natural language. The server never invents or silently guesses data.
  • 🔒 Safe by design — missing values are reported, never auto-filled. Only deterministic, reversible cleanup (duplicates, empty rows, whitespace, column names) is automated.
  • 🌐 Deploy-friendly — tools accept raw CSV text content, not local file paths, so the same server works locally and once deployed publicly (e.g. on Glama), where it has no access to your filesystem.

📁 Project Structure

csv-insight-mcp/
├── sample_data/
│   └── messy_sales.csv          # sample dataset for demos
├── src/
│   └── csvinsight/
│       ├── __init__.py          # package exports
│       ├── __main__.py          # `python -m csvinsight` entrypoint
│       └── server.py            # core server (Tools, Resources, Prompts)
├── tests/
│   └── test_server.py           # pytest smoke tests
├── .vscode/
│   └── mcp.json                 # VS Code Copilot Chat MCP config
├── pyproject.toml
└── README.md

📐 Architecture Overview

+-------------------------------------------------------------------------------+
|                                  MCP CLIENT                                   |
|         (VS Code Copilot Chat / Claude Desktop / Cursor IDE / Custom AI)      |
+-------------------------------------------------------------------------------+
                                       ▲
                                       │ JSON-RPC 2.0 (stdio)
                                       ▼
+-------------------------------------------------------------------------------+
|                       CSV INSIGHT & CLEANER MCP SERVER                        |
|                                                                                 |
|   [TOOLS]                     [RESOURCES]                 [PROMPTS]           |
|   • inspect_csv               • csv://current             • analyze_dataset   |
|   • summarize_csv               (dataset snapshot)         • clean_and_report |
|   • preview_csv               • csv://cleaning-report                        |
|   • clean_csv                   (before/after report)                        |
GitHub에서 전체 README 보기

설치

This server does not publish a one-line install command.

Open the repository installation guide MCP 초보자라면? mcpskill.org 가이드부터 시작하세요 →

설정

{ "mcpServers": { "csv-insight-cleaner": { "command": "python", "args": ["-m", "csvinsight"], "cwd": "/absolute/path/to/csv-insight-mcp" } } }