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Yandex Tracker MCP

issue_get_attachments

Retrieve attachments associated with a specific Yandex Tracker issue by providing its unique issue ID in the format '-'.

Instructions

Get attachments of a Yandex Tracker issue by its id

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
issue_idYesIssue ID in the format '<project>-<id>', like 'SOMEPROJECT-1'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The MCP tool handler function for 'issue_get_attachments'. Validates the issue_id against allowed queues and delegates the request to the underlying issues protocol.
    @mcp.tool(description="Get attachments of a Yandex Tracker issue by its id")
    async def issue_get_attachments(
        ctx: Context[Any, AppContext],
        issue_id: IssueID,
    ) -> list[IssueAttachment]:
        check_issue_id(settings, issue_id)
    
        return await ctx.request_context.lifespan_context.issues.issue_get_attachments(
            issue_id,
            auth=get_yandex_auth(ctx),
        )
  • Pydantic schema definition for the 'issue_id' input parameter of the tool.
    IssueID = Annotated[
        str,
        Field(description="Issue ID in the format '<project>-<id>', like 'SOMEPROJECT-1'"),
    ]
  • Registration of all MCP tools, including 'issue_get_attachments', by calling register_tools on the FastMCP server instance.
    register_tools(settings, mcp)
  • Helper function used by the handler to validate if the issue's queue is allowed per settings.
    def check_issue_id(settings: Settings, issue_id: str) -> None:
        queue, _ = issue_id.split("-")
        if settings.tracker_limit_queues and queue not in settings.tracker_limit_queues:
            raise IssueNotFound(issue_id)
  • Underlying implementation in TrackerClient that makes the HTTP GET request to the Yandex Tracker API endpoint for issue attachments.
    async def issue_get_attachments(
        self, issue_id: str, *, auth: YandexAuth | None = None
    ) -> list[IssueAttachment]:
        async with self._session.get(
            f"v3/issues/{issue_id}/attachments", headers=await self._build_headers(auth)
        ) as response:
            if response.status == 404:
                raise IssueNotFound(issue_id)
            response.raise_for_status()
            return IssueAttachmentList.model_validate_json(await response.read()).root
Behavior2/5

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 retrieves attachments but doesn't describe what 'attachments' entail (e.g., file types, size limits), whether it's a read-only operation, authentication needs, rate limits, or error handling. This leaves significant behavioral gaps for a tool that interacts with external data.

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 a single, direct sentence that efficiently conveys the core purpose without unnecessary words. It's front-loaded with the key action and resource, making it easy to parse and understand at a glance.

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 moderate complexity (retrieving issue attachments), the presence of an output schema reduces the need to describe return values. However, with no annotations and minimal behavioral context in the description, it's only adequate—the description covers the basic 'what' but lacks details on 'how' it behaves or integrates with siblings.

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

Parameters3/5

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

The schema description coverage is 100%, with the single parameter 'issue_id' fully documented in the schema (including format examples). The description adds no additional parameter semantics beyond implying the issue ID is required, so it meets the baseline score without compensating for any gaps.

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

Purpose4/5

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

The description clearly states the action ('Get attachments') and resource ('of a Yandex Tracker issue'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'issue_get_comments' or 'issue_get_links' that also retrieve issue-related data, which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing the issue ID), exclusions, or how it differs from similar tools like 'issue_get' (which might include attachments) or 'issue_get_comments', leaving the agent to infer usage context.

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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