Bridging AI and enterprise data with PromptQL x MCP
Blog post from Hasura
The PromptQL x MCP solution aims to bridge the gap between artificial intelligence (AI) and enterprise data by providing a unified data access layer. Currently, many organizations face challenges with implementing MCP due to technical limitations such as varied output structures, state management issues, LLM-dependent execution, and orchestration complexity. These challenges lead to difficulties in maintaining trust, reliability, and security. The PromptQL x MCP server solution proposes an alternative approach by treating the LLM as a planner rather than an executor, executing plans generated by the LLM through a unified data access layer provided by Hasura's Data Delivery Network (DDN). This approach enables fine-grained access control and governance, providing better security, accuracy, and developer experience. By integrating external MCP tools into a unified data graph, organizations can compose data from different sources in a single query, leading to improved outcomes. The solution offers a more structured planning and deterministic execution, resulting in higher accuracy, better security, and an improved developer experience.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| MCP | 15 | 3,982 | 251 | 105 | +75% |
| LLM | 11 | 5,029 | 781 | 224 | -11% |
| AI Agents | 2 | 2,792 | 485 | 163 | +5% |
| Developer Experience | 1 | 636 | 270 | 117 | +46% |
| Serverless | 1 | 1,647 | 334 | 115 | +98% |
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