YOKATLAS API MCP Server

Overview of YOKATLAS API MCP Server

YOKATLAS is the official platform that manages Turkey’s higher‑education licensing and pre‑licensing programs. The YOKATLAS API MCP server bridges this public data source with modern AI assistants by exposing the Python client through a FastMCP interface. Developers can therefore query licensing status, program details, and search results directly from a language model without writing custom API wrappers. This eliminates the need for repetitive HTTP requests and manual parsing, letting AI assistants deliver up‑to‑date information to end users in natural language.

The server provides a clean, typed MCP tool set that mirrors the underlying YOKATLAS API endpoints. Key capabilities include:

• License & Pre‑license Retrieval – Fetch detailed records for a specific applicant or program, including status, dates, and associated documents.
• Program Search (Wizard) – Perform keyword‑based searches across all licensing programs, returning ranked results that can be displayed in a user interface or summarized by the assistant.
• Data Normalization – The MCP layer automatically handles mapping of YOKATLAS response fields to concise, LLM‑friendly outputs, reducing cognitive load for model designers.

For developers building AI workflows, this server integrates seamlessly with any MCP‑compatible client. In Claude Desktop, a single configuration entry launches the server via , after which the assistant can invoke tools such as or . In other MCP ecosystems (e.g., 5ire), the same command line entry can be added under local tools, enabling cross‑model usage without additional code. This plug‑and‑play nature accelerates prototyping of educational tools, admissions chatbots, or compliance checkers.

Real‑world scenarios that benefit from YOKATLAS MCP include:

• University Admissions Portals – An assistant can instantly confirm a student’s license status or suggest next steps based on pre‑licensing results.
• Career Counseling Bots – Counselors can query program eligibility and graduation timelines to advise students accurately.
• Regulatory Audits – Internal audit tools can pull batch reports of licensing compliance, feeding the data into analytics pipelines.

What sets this MCP apart is its lightweight dependency on and FastMCP, ensuring fast startup times even in constrained environments. The server’s explicit mapping of YOKATLAS fields to human‑readable tool outputs gives developers full control over what the model sees, while still leveraging the robust data layer provided by . As a result, teams can rapidly build AI solutions that remain synchronized with Turkey’s official higher‑education licensing data.