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Automatically investigates app issues with root cause analysis across multiple systems.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Mida MCP Server" yet — see the docs or source repo.
Run a root cause analysis for the issue 'user sessions are not being recorded.' Check related logs, MongoDB records, Shopify events, and rrweb replay status. Identify the cause and provide fix recommendations and validation steps.
A structured investigation report identifying whether the cause is script failure, data write issues, or integration misconfiguration, with fixes and validation steps.
Analyze why the heatmap is empty. Cross-check application logs, event data in the database, Shopify page behavior information, and whether the rrweb data pipeline is working correctly. Output the conclusion and remediation priority.
A root cause determination for the missing heatmap data, such as missing tracking, incorrect event filtering, or corrupted replay data, plus remediation priority.
Perform automated root cause analysis for 'replica drift.' Check logs, MongoDB primary-replica status, related business data differences, and external platform events. Summarize the anomaly timeline and provide remediation advice.
An investigation output with the drift timeline, impact scope, likely triggers, and recommended actions to restore data consistency quickly.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.
Connect to e-commerce systems to query products, orders, and store data.
Track structured reasoning with confidence, branches, and revisions for complex problem solving.
Build, debug, and manage software tasks with natural language across LLMs.
Search, inspect, trace, and read business data assets across internal platforms.
Query and retrieve data across GitHub, Neo4j, PostgreSQL, and Milvus.