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Query and retrieve data across GitHub, Neo4j, PostgreSQL, and Milvus.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP Server" yet — see the docs or source repo.
Query the GitHub repository, Neo4j graph, PostgreSQL database, and Milvus vector store for code, entity relations, structured records, and similar documents related to "RAG performance optimization," then summarize the findings in a concise report.
A consolidated research report with key findings and a source-level overview.
Check a given user ID across PostgreSQL records, related Neo4j nodes, relevant GitHub change history, and similar cases in Milvus to identify possible data inconsistency issues.
An issue analysis showing linked data across systems and potential anomalies.
For the question "What key changes were recently made to our recommendation system?", retrieve relevant information from GitHub commits, Neo4j knowledge relations, PostgreSQL configuration data, and Milvus historical documents, then provide a timeline summary.
A timeline-based change summary with the relevant sources and key details.
Connect LLM apps to query and manage multiple databases through one tool.
Connect GitHub and local files to share standards, docs, and prompts with AI.
Connect AI assistants to PostgreSQL for secure querying, management, and analysis.
Manage GitHub repositories, pull requests, issues, and workflows with natural language.
Query and explore Neo4j graph databases with natural language and Cypher.
Connect and manage engineering, data, and collaboration platforms through natural language.