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glama

MCP Data Analyst

Enables natural language querying of SQL databases using AI, supporting multiple database types and automatic schema discovery.

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// key findings
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 2 credentials: LLM_API_KEY, DB_PASSWORD
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// required environment variables
This server reads these from process.env. You'll be asked to provide them before it can run.
🔐 secretLLM_API_KEYyour-api-key-here
configLLM_MODELgpt-3.5-turbo
configLLM_API_URL
configDB_TYPEmysql # mysqlpostgresqlmssqlmongodbsqlitessaselasticsearchinfluxdb
configDB_HOST"": "localhost",
configDB_PORT3306 # 5432 (PostgreSQL), 1433 (MSSQL), 27017 (MongoDB), 2383 (SSAS), 9200 (Elasticsearch), 8086 (InfluxDB)
configDB_USER
🔐 secretDB_PASSWORDyour-password
configDB_NAMEyour-database-name # For InfluxDB: database name; for SSAS/Elasticsearch: catalog/index database name
// full audit trail
The full breakdown of what we checked, the deductions that landed, the network hosts, the dependency advisories, and concrete fix guidance is available to verified publishers.
// improvement guidance — verified publishers only
We have 6 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
[![M8ven Score](https://m8ven.ai/badge/mcp/donmul-mcp-data-analyst-1xydfp)](https://m8ven.ai/mcp/donmul-mcp-data-analyst-1xydfp)
commit: 6d33fdca6e5c482bab4c3eaf0edd2b507cbfcb53
code hash: b7d852c684d64627590f27458cb697b727eb5fcec7c84eb7f5ed2f2fefd80c36
verified: 6/22/2026, 12:37:13 PM
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