UK Parliament MCP Server

get_lords_divisions_grouped_by_party

Group House of Lords divisions by party to analyze party-line voting and rebellions. Returns vote counts by party, not individual members.

Instructions

Get House of Lords divisions grouped by party | party-line voting, how parties voted, rebellions | Use when analyzing how different parties voted on issues | Returns vote counts by party rather than individual members.

    Args:
        search_term: Optional: search term for division topics (e.g. 'brexit', 'climate', 'NHS').
        member_id: Optional: only divisions this member voted in.
        start_date: Optional: start date in YYYY-MM-DD format.
        end_date: Optional: end date in YYYY-MM-DD format.
        division_number: Optional: specific division number.
        include_when_member_was_teller: Optional: include divisions where the member was a teller.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`end_date`	No
`member_id`	No
`start_date`	No
`search_term`	No
`division_number`	No
`include_when_member_was_teller`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 6, 2026

TDQS

A4.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose the output shape ('Returns vote counts by party rather than individual members'), which is useful behavioral context, but says nothing about pagination, result limits, defaults when no filters are supplied, or how filters combine. For a 6-param read tool with zero annotation coverage that is only partial disclosure.

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?

Front-loaded: the core purpose and its differentiator come first, followed by usage context, then a compact Args block. No filler sentences, though the per-parameter lines duplicate what ideally belongs in the schema and the multi-clause first line is slightly dense.

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

Completeness4/5

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

An output schema exists, so return-value detail is not required, and the description still summarizes the return shape. For a read-only filtering tool with no annotations, the main gaps are the absence of pagination/limit behavior and default filter semantics, but the essential call information is present.

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 0%, so the description must compensate, and it documents all six parameters, adding real meaning such as the YYYY-MM-DD date format (absent from the schema's plain 'string' type) and clarifying member_id scoping and the teller flag. The annotations are terse and largely restate parameter names, but every param gets coverage.

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?

States a specific verb and resource ('Get House of Lords divisions grouped by party') and immediately clarifies the distinguishing return shape: 'vote counts by party rather than individual members.' This separates it from siblings like search_lords_divisions and get_lords_division_by_id without opening either schema.

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?

Explicitly names the scenario: 'Use when analyzing how different parties voted on issues,' reinforced by tags like 'party-line voting, how parties voted, rebellions.' It does not state when NOT to use it or name alternatives (e.g., get_commons_divisions_grouped_by_party for the Commons, or search_lords_divisions for raw division lists), so it stops short of a 5.

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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