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* MCP Tool: track_mep_attendance
*
* Track and analyze MEP attendance patterns across plenary sessions
* with trend detection. Attendance is derived from votingStatistics
* (plenary vote participation); committee meeting attendance is not
* currently tracked.
*
* **Intelligence Perspective:** Attendance analysis reveals MEP engagement levels,
* potential disengagement signals, and participation patterns that correlate with
* political influence and legislative effectiveness.
*
* **Business Perspective:** Attendance tracking enables stakeholders to identify
* the most engaged and accessible MEPs for advocacy and outreach.
*
* ISMS Policy: SC-002 (Input Validation), AC-003 (Least Privilege)
*/
import { z } from 'zod';
import { epClient } from '../clients/europeanParliamentClient.js';
import type { ToolResult } from './shared/types.js';
/**
* Schema for track_mep_attendance tool input
*/
export const TrackMepAttendanceSchema = z.object({
mepId: z.string()
.min(1)
.max(100)
.optional()
.describe('MEP identifier (omit for group/country overview)'),
country: z.string()
.length(2)
.regex(/^[A-Z]{2}$/)
.optional()
.describe('Filter by country (ISO 3166-1 alpha-2)'),
groupId: z.string()
.min(1)
.max(50)
.optional()
.describe('Filter by political group'),
dateFrom: z.string()
.regex(/^\d{4}-\d{2}-\d{2}$/, 'Date must be in YYYY-MM-DD format')
.optional(),
dateTo: z.string()
.regex(/^\d{4}-\d{2}-\d{2}$/, 'Date must be in YYYY-MM-DD format')
.optional(),
limit: z.number()
.int()
.min(1)
.max(100)
.default(20)
.describe('Maximum number of MEPs to return')
});
/**
* MEP attendance record
*/
interface MepAttendanceRecord {
mepId: string;
mepName: string;
country: string;
politicalGroup: string;
attendanceRate: number;
totalSessions: number;
sessionsAttended: number;
trend: string;
category: string;
}
/**
* Attendance analysis result
*/
interface AttendanceAnalysis {
period: { from: string; to: string };
scope: string;
records: MepAttendanceRecord[];
summary: {
totalMEPs: number;
averageAttendance: number;
highAttendance: number;
mediumAttendance: number;
lowAttendance: number;
};
computedAttributes: {
overallEngagement: string;
attendanceTrend: string;
absenteeismRisk: string;
};
confidenceLevel: string;
dataFreshness: string;
sourceAttribution: string;
methodology: string;
}
/**
* Classify attendance category
*/
function classifyAttendance(rate: number): string {
if (rate >= 80) return 'HIGH';
if (rate >= 60) return 'MODERATE';
return 'LOW';
}
/**
* Determine attendance trend from rate
*/
function determineTrend(rate: number): string {
if (rate >= 85) return 'STABLE_HIGH';
if (rate >= 70) return 'STABLE';
if (rate >= 50) return 'DECLINING';
return 'CONCERNING';
}
/**
* Compute engagement level from average attendance
*/
function computeEngagement(avgRate: number): string {
if (avgRate >= 80) return 'HIGH';
if (avgRate >= 65) return 'MODERATE';
return 'LOW';
}
/**
* Compute absenteeism risk level
*/
function computeAbsenteeismRisk(lowCount: number, total: number): string {
if (total === 0) return 'UNKNOWN';
const ratio = lowCount / total;
if (ratio > 0.3) return 'HIGH';
Iif (ratio > 0.15) return 'MODERATE';
return 'LOW';
}
/**
* Build attendance record from MEP data
*/
function buildAttendanceRecord(
mep: {
id: string;
name: string;
country: string;
politicalGroup: string;
votingStatistics?: {
totalVotes: number;
attendanceRate: number;
};
}
): MepAttendanceRecord {
const hasStats = mep.votingStatistics !== undefined;
const rate = mep.votingStatistics?.attendanceRate ?? 0;
const total = mep.votingStatistics?.totalVotes ?? 0;
const attended = Math.round(total * (rate / 100));
return {
mepId: mep.id,
mepName: mep.name,
country: mep.country,
politicalGroup: mep.politicalGroup,
attendanceRate: rate,
totalSessions: total,
sessionsAttended: attended,
trend: hasStats ? determineTrend(rate) : 'UNKNOWN',
category: hasStats ? classifyAttendance(rate) : 'UNKNOWN'
};
}
/**
* Build attendance analysis for a single MEP
*/
async function buildSingleMepAnalysis(
mepId: string,
dateFrom: string,
dateTo: string
): Promise<AttendanceAnalysis> {
const mepData = await epClient.getMEPDetails(mepId);
const record = buildAttendanceRecord(mepData);
return {
period: { from: dateFrom, to: dateTo },
scope: `MEP ${mepData.name} (${mepData.id})`,
records: [record],
summary: {
totalMEPs: 1,
averageAttendance: record.attendanceRate,
highAttendance: record.category === 'HIGH' ? 1 : 0,
mediumAttendance: record.category === 'MODERATE' ? 1 : 0,
lowAttendance: record.category === 'LOW' ? 1 : 0
},
computedAttributes: {
overallEngagement: computeEngagement(record.attendanceRate),
attendanceTrend: record.trend,
absenteeismRisk: record.category === 'LOW' ? 'HIGH' : 'LOW'
},
confidenceLevel: 'HIGH',
dataFreshness: 'Real-time EP API data — MEP voting statistics from current EP records',
sourceAttribution: 'European Parliament Open Data Portal - data.europarl.europa.eu',
methodology: 'MEP attendance analysis using EP Open Data voting statistics. '
+ 'Data source: European Parliament Open Data Portal.'
};
}
/**
* Compute confidence level from data coverage ratio
*/
function computeConfidence(dataCoverage: number): string {
if (dataCoverage > 0.8) return 'HIGH';
Iif (dataCoverage > 0.4) return 'MEDIUM';
return 'LOW';
}
/**
* Fetch MEP details in batches to avoid overwhelming the EP API
*/
async function fetchMepDetailsBatched(
meps: { id: string }[],
batchSize: number
): Promise<NonNullable<Awaited<ReturnType<typeof epClient.getMEPDetails>>>[]> {
const details: NonNullable<Awaited<ReturnType<typeof epClient.getMEPDetails>>>[] = [];
for (let i = 0; i < meps.length; i += batchSize) {
const batch = meps.slice(i, i + batchSize);
const batchResults = await Promise.allSettled(
batch.map((mep) => epClient.getMEPDetails(mep.id))
);
for (const r of batchResults) {
if (r.status === 'fulfilled') {
details.push(r.value);
}
}
}
return details;
}
/**
* Build attendance analysis for multiple MEPs
*/
async function buildGroupAnalysis(
params: { country?: string; groupId?: string; limit: number },
dateFrom: string,
dateTo: string
): Promise<AttendanceAnalysis> {
const mepParams: Record<string, unknown> = { limit: params.limit };
if (params.country !== undefined) {
mepParams['country'] = params.country;
}
if (params.groupId !== undefined) {
mepParams['group'] = params.groupId;
}
const mepResult = await epClient.getMEPs(mepParams);
const meps = Array.isArray(mepResult.data) ? mepResult.data : [];
const details = await fetchMepDetailsBatched(
meps.slice(0, params.limit) as { id: string }[],
5
);
const records = details.map(d => buildAttendanceRecord(d));
records.sort((a, b) => b.attendanceRate - a.attendanceRate);
const totalMEPs = records.length;
const avgAttendance = totalMEPs > 0
? Math.round(records.reduce((s, r) => s + r.attendanceRate, 0) / totalMEPs * 100) / 100
: 0;
const high = records.filter(r => r.category === 'HIGH').length;
const medium = records.filter(r => r.category === 'MODERATE').length;
const low = records.filter(r => r.category === 'LOW').length;
const scopeParts: string[] = [];
if (params.country !== undefined) scopeParts.push(`Country: ${params.country}`);
if (params.groupId !== undefined) scopeParts.push(`Group: ${params.groupId}`);
const scope = scopeParts.length > 0 ? scopeParts.join(', ') : 'All MEPs';
const withStats = records.filter(r => r.totalSessions > 0).length;
const dataCoverage = totalMEPs > 0 ? withStats / totalMEPs : 0;
return {
period: { from: dateFrom, to: dateTo },
scope,
records,
summary: {
totalMEPs,
averageAttendance: avgAttendance,
highAttendance: high,
mediumAttendance: medium,
lowAttendance: low
},
computedAttributes: {
overallEngagement: computeEngagement(avgAttendance),
attendanceTrend: avgAttendance >= 70 ? 'STABLE' : 'DECLINING',
absenteeismRisk: computeAbsenteeismRisk(low, totalMEPs)
},
confidenceLevel: computeConfidence(dataCoverage),
dataFreshness: 'Real-time EP API data — MEP group attendance statistics from EP Open Data',
sourceAttribution: 'European Parliament Open Data Portal - data.europarl.europa.eu',
methodology: 'Group attendance analysis using EP Open Data voting statistics. '
+ 'Individual attendance rates derived from plenary vote participation. '
+ 'Data source: European Parliament Open Data Portal.'
};
}
/**
* Handles the track_mep_attendance MCP tool request.
*
* Tracks plenary attendance and participation rates for individual MEPs or groups
* of MEPs filtered by country or political group. Derives attendance metrics from
* plenary vote participation records and computes an overall attendance rating and
* trend for each MEP.
*
* @param args - Raw tool arguments, validated against {@link TrackMepAttendanceSchema}
* @returns MCP tool result containing individual MEP attendance rates, overall summary
* statistics, attendance trend classification, and computed participation scores
* @throws - If `args` fails schema validation (e.g., missing required fields or invalid format)
* - If the European Parliament API is unreachable or returns an error response
*
* @example
* ```typescript
* const result = await handleTrackMepAttendance({
* mepId: '124810',
* dateFrom: '2024-01-01',
* dateTo: '2024-12-31'
* });
* // Returns attendance analysis with participation rate, trend,
* // and session-level breakdown for the specified MEP
* ```
*
* @security - Input is validated with Zod before any API call.
* - Personal data in responses is minimised per GDPR Article 5(1)(c).
* - All requests are rate-limited and audit-logged per ISMS Policy AU-002.
* @since 0.8.0
* @see {@link trackMepAttendanceToolMetadata} for MCP schema registration
* @see [handleAssessMepInfluence](../../assessMepInfluence/functions/handleAssessMepInfluence.md) for comprehensive MEP influence and activity scoring
*/
export async function handleTrackMepAttendance(
args: unknown
): Promise<ToolResult> {
const params = TrackMepAttendanceSchema.parse(args);
const now = new Date();
const dateFrom = params.dateFrom ?? new Date(
now.getFullYear() - 1,
now.getMonth(),
now.getDate()
).toISOString().split('T')[0] ?? '';
const dateTo = params.dateTo ?? now.toISOString().split('T')[0] ?? '';
let analysis: AttendanceAnalysis;
if (params.mepId !== undefined) {
analysis = await buildSingleMepAnalysis(params.mepId, dateFrom, dateTo);
} else {
const groupParams: { country?: string; groupId?: string; limit: number } = {
limit: params.limit
};
if (params.country !== undefined) {
groupParams.country = params.country;
}
if (params.groupId !== undefined) {
groupParams.groupId = params.groupId;
}
analysis = await buildGroupAnalysis(groupParams, dateFrom, dateTo);
}
return {
content: [
{
type: 'text',
text: JSON.stringify(analysis, null, 2)
}
]
};
}
/**
* Tool metadata for MCP listing
*/
export const trackMepAttendanceToolMetadata = {
name: 'track_mep_attendance',
description: 'Track and analyze MEP attendance patterns across plenary sessions. Provides attendance rates, trends, and engagement categorization. Filter by individual MEP, country, or political group.',
inputSchema: {
type: 'object' as const,
properties: {
mepId: {
type: 'string',
description: 'MEP identifier (omit for group/country overview)'
},
country: {
type: 'string',
description: 'Filter by country (ISO 3166-1 alpha-2)'
},
groupId: {
type: 'string',
description: 'Filter by political group'
},
dateFrom: {
type: 'string',
description: 'Start date (YYYY-MM-DD)'
},
dateTo: {
type: 'string',
description: 'End date (YYYY-MM-DD)'
},
limit: {
type: 'number',
description: 'Maximum number of MEPs to return (default: 20)'
}
},
required: []
}
};
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