https://data-mentor.mcpize.run
Scanned Jun 3, 2026
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Your server uses protocol 2025-06-18. The latest version is 2025-11-25 with session management, origin validation, and notification support.
Server did not assign a session ID. Session management may not work.
Server does not validate Origin header — potential CSRF risk.
Custom domain: Default hosting subdomain
No authentication required — server is open to anonymous access, which may be intentional for public tools
Multiple similar MCP servers exist. Consider differentiating with unique features.
Unexpected response to SSE GET request: 200.
Server responded to ping
No Mcp-Session-Id assigned by server
Server correctly rejects invalid MCP-Protocol-Version with 400
Server correctly rejects malformed JSON-RPC with 400
Server returned 200 for invalid Origin (expected 403)
Server accepts DELETE for session termination (200)
Server returns 202 Accepted for JSON-RPC notifications
Server info: name, version
No OAuth? That's OK
OAuth is optional, but consider it for production deployments to protect your server from unauthorized access.
external: query, sql, table; LLM-native: format, parse, json
5+ similar servers — crowded space
Domain "sql" has broad developer audience
Competitors found
Built an MCP server that lets AI agents query your SQL database directly — schema, data, and performance analysis. Sharing something I built to ...
In this article, we'll explore the core components of a read-only data query and analysis MCP server, demonstrating how to combine SQL queries, ...
I'm having a hard time seeing the value of mCP for companies that rely heavily on data warehouse for cleaning and preparing data.
To your list I would also add using an MCP gateway or proxy to filter which tools are made available based on user and task type - although ...
An MCP (Model Context Protocol) server that provides a powerful tool to perform code reviews using various Large Language Models (LLMs).
“analyzeDataset: 30 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 15/20, Annot: 0/15”
“generateSqlQuery: 30 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 15/20, Annot: 0/15”
“generatePandasCode: 35 pts | Risk: unknown | Naming: 0/15, Desc: 15/20, Input: 15/20, Annot: 0/15”
“suggestVisualization: 35 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 20/20, Annot: 0/15”
“parseDatasetSchema: 30 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 15/20, Annot: 0/15”
“generateAnalysisPipeline: 35 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 20/20, Annot: 0/15”
“generateVSCodeConfig: 35 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 20/20, Annot: 0/15”
“generateJupyterHelperCode: 30 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 15/20, Annot: 0/15”
“generateTableauIntegration: 35 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 20/20, Annot: 0/15”
“generatePowerBIIntegration: 35 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 20/20, Annot: 0/15”
“generateMonitoringConfig: 35 pts | Risk: unknown | Naming: 0/15, Desc: 10/20, Input: 20/20, Annot: 0/15”
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