Bilka MCP Server

Bilka MCP Server

Bilka is a lightweight Model Context Protocol (MCP) server designed to bridge AI assistants with public web APIs. It addresses a common pain point for developers: the need to expose external data sources in a structured, secure, and reusable way without building bespoke integrations for each AI workflow. By presenting API endpoints as MCP tools, Bilka allows assistants such as Claude to query real‑world services—weather forecasts, stock prices, news feeds, or any RESTful resource—directly from within a conversation.

The server’s core value lies in its simplicity and flexibility. Developers configure the base URL of the target API and optionally set a custom user‑agent header, after which they can add new tools by writing an asynchronous Python function and decorating it with . The framework automatically handles request serialization, response parsing, and error propagation, so the assistant receives clean, typed outputs that can be referenced in subsequent prompts. This pattern eliminates repetitive boilerplate code and ensures consistent interaction patterns across different services.

Key capabilities include:

• Declarative tool definition: A single decorator exposes an async function as a callable MCP tool, making the codebase self‑documenting.
• Type‑safe communication: Full support for type hints and docstrings means that the assistant’s prompt engine can generate accurate signatures, improving developer experience.
• Central configuration: Global constants for the API base URL and user‑agent allow quick reconfiguration or environment switching without touching individual tools.
• Extensible architecture: Adding a new tool requires only one function; the server automatically registers it, reducing onboarding time for new APIs.

Typical use cases span from building a conversational data dashboard—where an assistant can pull live metrics on demand—to creating automated support agents that query ticketing systems or knowledge bases. In a CI/CD pipeline, Bilka can serve as an intermediary that translates structured queries from a model into API calls, aggregates results, and feeds them back for further reasoning. The server’s minimal footprint also makes it ideal for deployment in edge environments or as a local development stub that mimics external services.

What sets Bilka apart is its focus on rapid prototyping coupled with production readiness. The integration steps are intentionally straightforward: a single command to install dependencies, a minimal configuration file, and a clear pattern for extending functionality. Developers can spin up the server locally, connect it to Claude Desktop via a simple JSON entry, and immediately start leveraging external data in their conversations. This tight coupling between MCP tooling and AI workflows empowers teams to iterate faster, maintain cleaner codebases, and deliver richer, data‑driven conversational experiences.