Fibery MCP Server

The Fibery MCP Server bridges the gap between an AI assistant and a Fibery workspace, enabling developers to harness natural‑language interactions for data retrieval, creation, and modification without leaving the assistant’s interface. By exposing Fibery’s rich relational data model through the Model Context Protocol, it transforms routine database operations into conversational tasks that can be orchestrated by an LLM such as Claude.

At its core, the server solves a common pain point: developers and power users often need to query or manipulate Fibery entities while drafting notes, building workflows, or brainstorming ideas. Traditionally this requires switching to the web UI or writing custom API calls. The MCP server eliminates that friction by offering a set of well‑defined tools—, , , , , and —that an AI can invoke directly from a chat. The assistant interprets user intent, calls the appropriate tool, and returns results in natural language, all while maintaining context across turns.

Key capabilities include:

• Intuitive data exploration: Users can ask questions like “Show me all databases that track project status” and receive a concise list without manual filtering.
• Schema awareness: The tool reveals field titles, names, and types, allowing the assistant to guide users in constructing accurate queries or updates.
• Flexible querying: With , developers can leverage Fibery’s query language through natural‑language prompts, enabling complex filters, sorting, and aggregation without writing code.
• Entity lifecycle management: and let users add or modify records on the fly, while supports bulk operations for data migration or bulk updates.

In real‑world scenarios, a product manager could draft a sprint plan in the assistant, then ask it to create corresponding Fibery tasks and link them to the appropriate project database. A data analyst might request a summary of sales figures, have the assistant query Fibery, and then generate a report—all within a single conversational session. The server’s tight integration with the MCP client config means it can be plugged into any LLM that supports the protocol, making it a versatile addition to automated workflows.

What sets Fibery MCP Server apart is its conversational data engineering approach. Rather than exposing raw API endpoints, it presents a curated set of tools that respect Fibery’s relational structure while remaining accessible to non‑technical users. This design reduces cognitive load, speeds up iteration cycles, and empowers teams to embed Fibery data deeper into their AI‑driven processes.