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Jij MCP Server

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by Jij-Inc

qiskit_v1_api_reference_toc

Fetch the Qiskit v1 API reference table of contents in Markdown format to navigate quantum computing documentation efficiently.

Instructions

Fetch the Qiskit v1 API reference table of contents (https://docs.quantum.ibm.com/api/qiskit/1.4).
Returns:
    str: The table of contents in Markdown format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'qiskit_v1_api_reference_toc' tool. It fetches the table of contents from the Qiskit v1 API documentation URL using the fetch_as_markdown helper and returns it in Markdown format, handling errors appropriately.
    @mcp.tool()
    async def qiskit_v1_api_reference_toc() -> str:
        """
        Fetch the Qiskit v1 API reference table of contents (https://docs.quantum.ibm.com/api/qiskit/1.4).
        Returns:
            str: The table of contents in Markdown format.
        """
        url = "https://docs.quantum.ibm.com/api/qiskit/1.4"
        response: FetchResponse = await fetch_as_markdown(url)
        if response.isError:
            return response.errorMessage if response.errorMessage else "Error fetching the content"
        return url + "\n" + response.content[0]["text"]
  • The @mcp.tool() decorator registers the qiskit_v1_api_reference_toc function as an MCP tool.
    @mcp.tool()
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 of behavioral disclosure. It states the tool fetches content from a specific URL and returns Markdown format, which covers the basic operation and output type. However, it lacks details on error handling, rate limits, authentication needs, or whether the fetch is cached or real-time, leaving behavioral gaps for a tool that interacts with external resources.

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 extremely concise and front-loaded, consisting of only two sentences that directly state what the tool does and what it returns. Every sentence earns its place by providing essential information without any redundancy or fluff, making it highly efficient for an AI agent to parse.

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

Completeness3/5

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

Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is complete enough for basic understanding. It specifies the exact resource and output format. However, for a tool that fetches from an external URL, additional context on reliability, error cases, or caching behavior would enhance completeness, especially since there are no annotations to cover these aspects.

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?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description does not need to add parameter semantics, so it meets the baseline of 4 for tools with no parameters, as it appropriately focuses on the tool's purpose and output without unnecessary parameter details.

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 specific action ('Fetch') and resource ('Qiskit v1 API reference table of contents') with the exact URL provided. It distinguishes from siblings like 'qiskit_v2_api_reference_toc' by specifying the v1 version, and from 'qiskit_tutorial' by focusing on API reference documentation rather than tutorials.

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

Usage Guidelines3/5

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

The description implies usage context by specifying the exact URL and version (v1), suggesting it should be used for Qiskit v1 API documentation needs. However, it does not explicitly state when to use this tool versus alternatives like 'qiskit_v2_api_reference_toc' or 'fetch_as_markdown', nor does it provide any exclusion criteria or prerequisites.

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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