Firebird MCP Server

The Firebird MCP Server gives large‑language models instant, read‑only access to Firebird databases. By exposing a lightweight protocol that exposes schema information and allows safe execution of SELECT statements, it removes the need for developers to write custom connectors or worry about query injection when an AI assistant needs to read data from a legacy Firebird instance. This is particularly valuable for teams that want AI‑powered analytics, data exploration or conversational interfaces without compromising database security.

The server works by launching a Docker container (or running via NPX) that hosts the Firebird engine and serves it through the Model Context Protocol. Once connected, the MCP client can request a table’s schema via a simple URL such as . The response is a JSON object that lists column names and data types, automatically pulled from the database metadata. For querying, the server offers a single tool named query that accepts an arbitrary SQL string and executes it inside a read‑only transaction. Because every query runs in a non‑committable context, there is no risk of accidental data modification or transaction locking.

Key capabilities include:

• Schema discovery: Developers can programmatically retrieve table structures, making it easy to generate prompts or UI forms that reflect the underlying data.
• Safe query execution: The read‑only transaction guarantees that no writes occur, allowing developers to let the AI run exploratory SELECTs without permission concerns.
• Docker‑friendly deployment: The server can be spun up with a single command, making it trivial to integrate into CI/CD pipelines or local development environments.
• Credential handling: Usernames and passwords can be embedded in the connection URL, simplifying authentication for non‑interactive use cases.

Typical use cases involve building conversational data assistants that answer questions about sales records, inventory levels, or customer profiles stored in Firebird. For example, a business analyst could ask the AI to “list all customers who purchased more than $5,000 last quarter,” and the assistant would generate the SQL, run it via the MCP server, and return a formatted result. Another scenario is automated report generation: an AI could pull schema information to construct dynamic dashboards or export CSV files without manual scripting.

Integrating the Firebird MCP Server into an AI workflow is straightforward. A Claude Desktop or other MCP‑compatible client adds the server to its configuration, and then developers can reference the query tool or schema resources directly in prompts. The server’s read‑only nature means it can be safely exposed to public or semi‑public AI agents, providing powerful data insights while preserving database integrity. The combination of schema introspection and controlled query execution makes the Firebird MCP Server a unique, low‑maintenance bridge between legacy databases and modern AI assistants.