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Get tenant scoping context

get_tenant_context
Read-onlyIdempotent

Retrieve the tenant or account scope attributed to the current API call. Use this to verify which multi-tenant context the server assigned to your session.

Instructions

Return the multi-tenant scoping context of the current call.

Use this to confirm which tenant/account scope the server attributes
the session to. On the streamable-HTTP transport (D7, #42) the
``tenant`` field carries the value of the optional
``Camt053-Account`` request header the caller sent; over stdio (or
when the caller sent no header) it is ``None``. The same value is
stamped as the ``scope`` on the server's audit log, so an agent can
verify its calls are attributed to the right tenant.

The lookup is read-only and deterministic for a given request:
nothing is validated or mutated, and no external system is touched.

Args:
    ctx: The FastMCP Context (auto-injected; carries the underlying
        HTTP request, when there is one).

Returns:
    ``{"service": "camt053-mcp", "tenant": str | None}``.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by stating 'nothing is validated or mutated, and no external system is touched,' which reinforces the safe, deterministic nature. No contradiction with annotations.

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

Conciseness4/5

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

The description is well-structured with clear sections (Args, Returns). It is slightly verbose with transport-specific details ('D7, #42'), but each sentence adds context. Could be more concise, but still effective and front-loaded.

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 zero parameters, existing annotations, and no output schema (but the description provides the exact return format), the description is fully complete. It explains behavior, transport variants, return structure, and use case.

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?

There are zero parameters, so schema coverage is 100% (empty). The description does not need to add parameter meaning. It explains the return format, which is helpful for understanding the output. Baseline 4 is appropriate.

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 tool returns the multi-tenant scoping context. It uses specific verbs ('return') and identifies the resource ('multi-tenant scoping context'), distinguishing it from sibling tools like 'list_entries' or 'validate_records' which serve different purposes.

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 explicitly says to use this tool 'to confirm which tenant/account scope the server attributes the session to.' It also explains behavior differences between transports, but does not explicitly mention when not to use it or compare to alternatives; however, given its unique diagnostic function, this is clear enough.

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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