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paulieb89

UK Legal Research MCP Server

Get Member Debates

parliament_member_debates
Read-onlyIdempotent

Search a specific MP's Hansard contributions for a verbatim phrase. Enter a member ID and optional topic to retrieve only speeches containing that exact wording.

Instructions

USE THIS TOOL WHEN you have a member_id and want contributions where THAT member used a specific topic phrase verbatim (text-body search).

CALL parliament_find_member(name) FIRST to obtain the integer member_id.

This is a name-based text-body search — it matches contributions whose TEXT contains the topic phrase. A member who spoke in a debate but didn't use your phrase verbatim is filtered out. For verbatim retrieval of every contribution by a member in a known debate (regardless of vocabulary), use parliament_get_debate_contributions(debate_ext_id, member_id=...) instead.

Each contribution's text field is capped at 3000 characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
member_idYesParliament Members API integer ID. Obtain from parliament_find_member.
topicNoOptional phrase to find in THIS member's contribution text bodies. Hansard searches the words the member actually said, NOT the topic or title of the debate. Pass tokens this member would have spoken — distinctive arguments ('disproportionate sanction'), statutory references ('section 21'), or motion numbers ('Motion C1') — not the bill's name (members rarely say e.g. 'Renters\' Rights Bill' verbatim in their speeches). If you want 'every contribution this member made in a specific debate' regardless of words used, find the debate_ext_id then use parliament_get_debate_contributions(debate_ext_id, member_id=...).
offsetNoNumber of contributions to skip before this page. Default 0. Re-call with offset=offset+returned while has_more is true.
limitNoMaximum contributions to return. Default 20.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
member_idYesParliament Members API member ID
topicNoTopic phrase filter applied, if any
offsetNoSkip applied to this page
limitNoPage size requested
totalYesNumber of contributions returned in this call
has_moreNoTrue if a full page was returned (more may exist)
contributionsNoHansard contributions for the member. Each `text` field is capped at 3000 characters.
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false. Description adds that text is capped at 3000 characters, explains the text-body search nature, and clarifies filtering behavior. No contradictions.

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?

Well-structured with clear sections, but could be slightly more concise. Still, every sentence adds value and front-loads purpose.

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?

Covers purpose, parameters, usage guidelines, behavioral quirks (text cap), pagination, and references sibling tools. Adequate for a tool with 4 params and output schema.

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

Parameters5/5

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

Schema coverage is 100%, but description adds valuable context for 'topic' parameter (e.g., what phrases to search, avoid bill names) and explains offset pagination. Significantly enhances schema.

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 starts with 'USE THIS TOOL WHEN...' and clearly states the verb (get contributions), resource (member contributions by topic phrase), and differentiates from sibling tool parliament_get_debate_contributions.

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

Usage Guidelines5/5

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

Provides explicit when to use (having member_id and wanting contributions with specific phrase) and when not to use (for all contributions regardless of vocabulary, use parliament_get_debate_contributions). Also gives prerequisite to call parliament_find_member first.

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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