Data Recon Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Data Recon Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
An MCP (Model Context Protocol) server for data reconciliation between MySQL and Snowflake databases. Enables LLM agents like Claude, Antigravity, and Perplexity to validate data integrity during migrations, ETL processes, and ongoing monitoring.
pip install data-recon-mcpAdd to your MCP client configuration:
For Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"data-recon": {
"command": "python3",
"args": ["-m", "mcp_server"]
}
}
}For Antigravity (~/.gemini/antigravity/mcp_config.json):
{
"data-recon": {
"command": "python3",
"args": ["-m", "mcp_server"]
}
}For Perplexity (MCP Settings):
{
"data-recon": {
"command": "python3",
"args": ["-m", "mcp_server"]
}
}That's it! Restart your LLM client and start using the tools.
For team environments where you want everyone to share the same datasources:
1. Start the centralized backend:
git clone https://github.com/hindocharaj1997/data-recon-mcp.git
cd data-recon-mcp
pip install -e .
uvicorn data_recon.main:app --host 0.0.0.0 --port 80002. Configure clients to use it:
{
"data-recon": {
"command": "python3",
"args": ["-m", "mcp_server"],
"env": {
"FASTAPI_URL": "http://your-server.company.com:8000"
}
}
}Register data sources via environment variables:
{
"data-recon": {
"command": "python3",
"args": ["-m", "mcp_server"],
"env": {
"DATASOURCE_MYSQL_PROD": "{\"type\":\"mysql\",\"host\":\"localhost\",\"port\":3306,\"username\":\"user\",\"password\":\"pass\",\"database\":\"mydb\"}"
}
}
}| Category | Tools | Description |
|---|---|---|
| Data Source Management | 7 | Add, list, test, remove datasources |
| Discovery & Validation | 7 | Search tables, validate existence, preview data |
| Individual Checks | 4 | Row count, aggregates, schema, sample rows |
| Job Management | 5 | Create/monitor reconciliation jobs |
add_datasource - Register a MySQL or Snowflake connectionsearch_tables - Find tables by patternrun_row_count_check - Compare row counts between source and targetrun_aggregate_check - Compare SUM, AVG, MIN, MAX valuescreate_recon_job - Run comprehensive reconciliation with all checks┌─────────────────────────────────────────────────────────┐
│ LLM Client │
│ (Claude, Antigravity, etc.) │
└─────────────────────┬───────────────────────────────────┘
│ MCP Protocol (stdio)
▼
┌─────────────────────────────────────────────────────────┐
│ MCP Server │
│ (python3 -m mcp_server) │
├─────────────────────────────────────────────────────────┤
│ Embedded FastAPI Backend (or external via FASTAPI_URL) │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │
│ │ SQLite │ │ MySQL │ │ Snowflake │ │
│ │ (metadata) │ │ Connector │ │ Connector │ │
│ └─────────────┘ └─────────────┘ └─────────────────┘ │
└─────────────────────────────────────────────────────────┘# Clone and setup
git clone https://github.com/hindocharaj1997/data-recon-mcp.git
cd data-recon-mcp
pip install -e ".[dev]"
# Run tests
pytest
# Start local MySQL for testing
docker compose -f tests/docker-compose.yml up -dMIT
Contributions welcome! Please open an issue first to discuss proposed changes.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.