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saidsurucu

YOKATLAS API MCP Server

by saidsurucu

get_bachelor_degree_atlas_details

Retrieve detailed information about specific bachelor's degree programs in Turkey, including statistics, quotas, placement data, and academic details using YÖP codes and year parameters.

Instructions

Get comprehensive details for a specific bachelor's degree program from YOKATLAS Atlas.

Parameters:

  • yop_kodu (str): Program YÖP code (e.g., '102210277')

  • year (int): Data year (e.g., 2024, 2023)

Returns detailed information including:

  • General program information and statistics

  • Quota, placement, and score data

  • Student demographics and distribution

  • Academic staff and facility information

  • Historical placement trends

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yop_koduYesProgram YÖP code (e.g., '102210277') - unique identifier for the bachelor's degree program
yearYesData year for statistics (e.g., 2024, 2023)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function implementing the tool logic for fetching bachelor's degree program details from YOKATLAS Atlas. Includes @mcp.tool() decorator for registration and Pydantic Field annotations for input schema validation.
    @mcp.tool()
    async def get_bachelor_degree_atlas_details(
        yop_kodu: Annotated[str, Field(description="Program YÖP code (e.g., '102210277') - unique identifier for the bachelor's degree program")],
        year: Annotated[int, Field(description="Data year for statistics (e.g., 2024, 2023)", ge=2020, le=2030)]
    ) -> dict:
        """
        Get comprehensive details for a specific bachelor's degree program from YOKATLAS Atlas.
    
        Parameters:
        - yop_kodu (str): Program YÖP code (e.g., '102210277')
        - year (int): Data year (e.g., 2024, 2023)
    
        Returns detailed information including:
        - General program information and statistics
        - Quota, placement, and score data
        - Student demographics and distribution
        - Academic staff and facility information
        - Historical placement trends
        """
        try:
            lisans_atlasi = YOKATLASLisansAtlasi({'program_id': yop_kodu, 'year': year})
            result = await lisans_atlasi.fetch_all_details()
            return result
        except Exception as e:
            print(f"Error in get_bachelor_degree_atlas_details: {e}")
            return {"error": str(e), "program_id": yop_kodu, "year": year}
  • Registration of the tool using FastMCP's @mcp.tool() decorator.
    @mcp.tool()
  • Input schema defined using Annotated with Pydantic Field for parameter validation and descriptions.
        yop_kodu: Annotated[str, Field(description="Program YÖP code (e.g., '102210277') - unique identifier for the bachelor's degree program")],
        year: Annotated[int, Field(description="Data year for statistics (e.g., 2024, 2023)", ge=2020, le=2030)]
    ) -> dict:
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It indicates this is a read operation ('Get') and lists the types of information returned, but doesn't disclose behavioral traits like rate limits, authentication needs, error conditions, or whether the data is real-time vs. cached. It adds some context about what data is included but lacks operational details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose. It uses bullet points efficiently to detail return information without redundancy. Every sentence earns its place by clarifying scope and outputs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, read-only), 100% schema coverage, and the presence of an output schema (implied by 'Returns detailed information'), the description is complete enough. It specifies the resource scope, parameters, and return data types, which aligns well with the structured data provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds minimal value by listing parameters and providing examples, but doesn't explain semantics beyond what's in the schema (e.g., what YÖP code format entails). Baseline is 3, but it gets a point for reinforcing parameter importance with the examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get comprehensive details' and specifies the resource as 'a specific bachelor's degree program from YOKATLAS Atlas.' It distinguishes from sibling tools by focusing on bachelor's degree programs (vs. associate degree tools) and on retrieving details for a specific program (vs. search tools).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying it's for retrieving details of a specific bachelor's degree program, which differentiates it from search tools. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_bachelor_degree_programs' or provide exclusions (e.g., not for associate degrees).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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