diff --git a/services/mcp-server/src/modules/a2a/keyboard-diagnostics-pipeline.ts b/services/mcp-server/src/modules/a2a/keyboard-diagnostics-pipeline.ts
new file mode 100644
index 00000000..c660e356
--- /dev/null
+++ b/services/mcp-server/src/modules/a2a/keyboard-diagnostics-pipeline.ts
@@ -0,0 +1,282 @@
+/**
+ * KeyboardDiagnosticsAgent — A2A pipeline for LysnrAI iOS keyboard extension diagnostics.
+ *
+ * Agent roster (3 steps):
+ *   1. KeyboardErrorScannerAgent — query telemetry for 'error' events from keyboard install IDs
+ *   2. DiagnosticsSessionAgent   — open a diagnostics session targeting each erroring installId
+ *   3. BugReportDraftAgent       — assemble structured bug report per install ID with error details
+ *
+ * MCP tools:
+ *   lysnrai.keyboard.diagnose(from?, to?, minErrors?) — run pipeline
+ */
+
+import { randomUUID } from 'node:crypto';
+import { z } from 'zod';
+import { registerTool } from '../tools/registry.js';
+import type { McpToolRequest } from '../tools/types.js';
+import {
+  telemetryQuery,
+  diagnosticsCreateSession,
+  diagnosticsUpdateSession,
+  type DebugSession,
+} from '../../lib/platform-client.js';
+
+// ── Types ──────────────────────────────────────────────────────────────────────
+
+interface KeyboardErrorGroup {
+  anonymousInstallId: string;
+  errorCount: number;
+  errorTypes: string[];
+  firstSeen: string;
+  lastSeen: string;
+  rawEvents: Array<Record<string, unknown>>;
+}
+
+interface DiagnosticsResult {
+  anonymousInstallId: string;
+  session: DebugSession | null;
+  skipReason?: string;
+}
+
+interface BugReportDraft {
+  anonymousInstallId: string;
+  diagnosticsSessionId: string | null;
+  errorCount: number;
+  errorTypes: string[];
+  firstSeen: string;
+  lastSeen: string;
+  reproSteps: string;
+  severity: 'critical' | 'high' | 'medium';
+}
+
+export interface KeyboardDiagnosticsReport {
+  runId: string;
+  productId: 'lysnrai';
+  from: string;
+  to: string;
+  installsScanned: number;
+  erroringInstalls: number;
+  diagnosticsOpened: number;
+  bugReports: BugReportDraft[];
+  summary: string;
+  generatedAt: string;
+}
+
+// ── Step 1: KeyboardErrorScannerAgent ─────────────────────────────────────────
+
+async function scanKeyboardErrors(
+  fromTime: string,
+  toTime: string,
+  minErrors: number,
+  opts: { token?: string; requestId?: string }
+): Promise<KeyboardErrorGroup[]> {
+  const installMap = new Map<string, KeyboardErrorGroup>();
+
+  try {
+    const result = await telemetryQuery(
+      {
+        productId: 'lysnrai',
+        eventType: 'error',
+        from: fromTime,
+        to: toTime,
+        limit: 500,
+      },
+      { ...opts, productId: 'lysnrai' }
+    );
+
+    const events = result.events as Array<Record<string, unknown>>;
+
+    for (const event of events) {
+      const props = (event['properties'] as Record<string, unknown>) ?? {};
+      const surface = String(props['surface'] ?? event['surface'] ?? '').toLowerCase();
+      if (!surface.includes('keyboard')) continue;
+
+      const installId = String(
+        props['anonymousInstallId'] ??
+          event['anonymousId'] ??
+          event['anonymousInstallId'] ??
+          'unknown'
+      );
+      const errorType = String(
+        props['errorType'] ?? props['error_type'] ?? event['eventType'] ?? 'unknown'
+      );
+      const timestamp = String(
+        event['timestamp'] ?? event['createdAt'] ?? new Date().toISOString()
+      );
+
+      const group = installMap.get(installId) ?? {
+        anonymousInstallId: installId,
+        errorCount: 0,
+        errorTypes: [],
+        firstSeen: timestamp,
+        lastSeen: timestamp,
+        rawEvents: [],
+      };
+
+      group.errorCount++;
+      if (!group.errorTypes.includes(errorType)) group.errorTypes.push(errorType);
+      if (timestamp < group.firstSeen) group.firstSeen = timestamp;
+      if (timestamp > group.lastSeen) group.lastSeen = timestamp;
+      group.rawEvents.push(event);
+
+      installMap.set(installId, group);
+    }
+  } catch {
+    // best-effort
+  }
+
+  return Array.from(installMap.values()).filter(g => g.errorCount >= minErrors);
+}
+
+// ── Step 2: DiagnosticsSessionAgent ───────────────────────────────────────────
+
+async function openDiagnosticsSession(
+  group: KeyboardErrorGroup,
+  opts: { token?: string; requestId?: string }
+): Promise<DiagnosticsResult> {
+  try {
+    const session = await diagnosticsCreateSession(
+      {
+        productId: 'lysnrai',
+        targetAnonymousId: group.anonymousInstallId,
+        collectionLevel: 'debug',
+        captureLogs: true,
+      },
+      opts
+    );
+    return { anonymousInstallId: group.anonymousInstallId, session };
+  } catch (err) {
+    return {
+      anonymousInstallId: group.anonymousInstallId,
+      session: null,
+      skipReason: err instanceof Error ? err.message : String(err),
+    };
+  }
+}
+
+// ── Step 3: BugReportDraftAgent ───────────────────────────────────────────────
+
+async function closeDiagnosticsAndDraft(
+  group: KeyboardErrorGroup,
+  diagnosticsResult: DiagnosticsResult,
+  opts: { requestId?: string }
+): Promise<BugReportDraft> {
+  if (diagnosticsResult.session) {
+    try {
+      await diagnosticsUpdateSession(diagnosticsResult.session.id, { status: 'completed' }, opts);
+    } catch {
+      // best-effort
+    }
+  }
+
+  const severity: 'critical' | 'high' | 'medium' =
+    group.errorCount >= 10 ? 'critical' : group.errorCount >= 5 ? 'high' : 'medium';
+
+  const reproSteps = [
+    `1. Open LysnrAI iOS keyboard extension on device with installId ${group.anonymousInstallId}.`,
+    `2. Trigger dictation — error types observed: ${group.errorTypes.join(', ')}.`,
+    `3. First seen ${group.firstSeen}, last seen ${group.lastSeen} (${group.errorCount} occurrences).`,
+    diagnosticsResult.session
+      ? `4. Diagnostics session ${diagnosticsResult.session.id} opened — check logs for stack traces.`
+      : '4. Diagnostics session could not be opened automatically.',
+  ].join('\n');
+
+  return {
+    anonymousInstallId: group.anonymousInstallId,
+    diagnosticsSessionId: diagnosticsResult.session?.id ?? null,
+    errorCount: group.errorCount,
+    errorTypes: group.errorTypes,
+    firstSeen: group.firstSeen,
+    lastSeen: group.lastSeen,
+    reproSteps,
+    severity,
+  };
+}
+
+// ── Pipeline runner ────────────────────────────────────────────────────────────
+
+async function runKeyboardDiagnosticsPipeline(
+  fromTime: string,
+  toTime: string,
+  minErrors: number,
+  req: McpToolRequest
+): Promise<KeyboardDiagnosticsReport> {
+  const runId = randomUUID();
+  const opts = { token: req.headers.authorization?.slice(7), requestId: req.id };
+
+  req.log.info(
+    { runId, stepId: 'scan', fromTime, toTime, minErrors },
+    'KeyboardErrorScannerAgent start'
+  );
+  const errorGroups = await scanKeyboardErrors(fromTime, toTime, minErrors, opts);
+  req.log.info(
+    { runId, stepId: 'scan', erroringInstalls: errorGroups.length },
+    'KeyboardErrorScannerAgent done'
+  );
+
+  req.log.info(
+    { runId, stepId: 'diagnostics', count: errorGroups.length },
+    'DiagnosticsSessionAgent start'
+  );
+  const diagnosticsResults: DiagnosticsResult[] = [];
+  for (const group of errorGroups) {
+    const result = await openDiagnosticsSession(group, opts);
+    diagnosticsResults.push(result);
+  }
+  const opened = diagnosticsResults.filter(r => r.session !== null).length;
+  req.log.info({ runId, stepId: 'diagnostics', opened }, 'DiagnosticsSessionAgent done');
+
+  req.log.info({ runId, stepId: 'draft', count: errorGroups.length }, 'BugReportDraftAgent start');
+  const bugReports: BugReportDraft[] = [];
+  for (let i = 0; i < errorGroups.length; i++) {
+    const draft = await closeDiagnosticsAndDraft(errorGroups[i]!, diagnosticsResults[i]!, {
+      requestId: req.id,
+    });
+    bugReports.push(draft);
+  }
+
+  const summary =
+    errorGroups.length === 0
+      ? `No keyboard errors with >= ${minErrors} occurrence(s) found in the specified window.`
+      : `${errorGroups.length} install(s) with keyboard errors detected. ${opened} diagnostics session(s) opened. ${bugReports.filter(r => r.severity === 'critical').length} critical, ${bugReports.filter(r => r.severity === 'high').length} high severity.`;
+
+  req.log.info({ runId, stepId: 'draft', summary }, 'BugReportDraftAgent done');
+
+  return {
+    runId,
+    productId: 'lysnrai',
+    from: fromTime,
+    to: toTime,
+    installsScanned: errorGroups.length,
+    erroringInstalls: errorGroups.length,
+    diagnosticsOpened: opened,
+    bugReports,
+    summary,
+    generatedAt: new Date().toISOString(),
+  };
+}
+
+// ── MCP tool registration ─────────────────────────────────────────────────────
+
+registerTool({
+  name: 'lysnrai.keyboard.diagnose',
+  description:
+    'A2A pipeline: scans LysnrAI telemetry for error events from the iOS keyboard extension, groups errors by anonymousInstallId, opens a diagnostics session per affected install, and drafts a structured bug report. Returns severity-ranked reports with repro steps. Requires admin role.',
+  requiredRole: 'admin',
+  inputSchema: z.object({
+    from: z.string().datetime().optional().describe('Start of telemetry window (default: 48h ago)'),
+    to: z.string().datetime().optional().describe('End of telemetry window (default: now)'),
+    minErrors: z.coerce
+      .number()
+      .int()
+      .min(1)
+      .default(3)
+      .describe('Minimum error count per install to include in report (default 3)'),
+  }),
+  async execute(args, req) {
+    const now = new Date();
+    const toTime = args.to ?? now.toISOString();
+    const fromTime = args.from ?? new Date(now.getTime() - 48 * 60 * 60 * 1000).toISOString();
+    return runKeyboardDiagnosticsPipeline(fromTime, toTime, args.minErrors, req);
+  },
+});
diff --git a/services/mcp-server/src/modules/a2a/nl-parser-eval-pipeline.ts b/services/mcp-server/src/modules/a2a/nl-parser-eval-pipeline.ts
new file mode 100644
index 00000000..e8d8ecbf
--- /dev/null
+++ b/services/mcp-server/src/modules/a2a/nl-parser-eval-pipeline.ts
@@ -0,0 +1,266 @@
+/**
+ * NLParserEvalAgent — A2A pipeline for ChronoMind natural-language timer parsing evaluation.
+ *
+ * Agent roster (3 steps):
+ *   1. PhraseSamplerAgent   — assemble canonical NL phrase test suite
+ *   2. ParseEvalAgent       — run each phrase through extraction service 'timer-parse' task
+ *   3. RegressionReportAgent — validate parsed fields, flag failures, produce pass/fail scorecard
+ *
+ * MCP tools:
+ *   chronomind.nlParser.eval(customPhrases?) — run eval pipeline; returns pass/fail scorecard
+ */
+
+import { randomUUID } from 'node:crypto';
+import { z } from 'zod';
+import { registerTool } from '../tools/registry.js';
+import type { McpToolRequest } from '../tools/types.js';
+import { extractionRun } from '../../lib/extraction-client.js';
+
+// ── Canonical test suite ──────────────────────────────────────────────────────
+
+interface NLTestCase {
+  phrase: string;
+  expectedFields: string[];
+  description: string;
+}
+
+const CANONICAL_TEST_CASES: NLTestCase[] = [
+  {
+    phrase: 'Remind me in 30 minutes',
+    expectedFields: ['duration'],
+    description: 'Simple countdown',
+  },
+  {
+    phrase: 'Wake me up at 7am tomorrow',
+    expectedFields: ['targetTime'],
+    description: 'Alarm at specific time',
+  },
+  {
+    phrase: 'Meeting in 2 hours and 15 minutes',
+    expectedFields: ['duration'],
+    description: 'Compound duration',
+  },
+  {
+    phrase: 'Call mom every day at 6pm',
+    expectedFields: ['targetTime', 'recurrence'],
+    description: 'Recurring alarm',
+  },
+  {
+    phrase: 'Study session for 45 minutes then break for 10',
+    expectedFields: ['duration'],
+    description: 'Linked timers',
+  },
+  {
+    phrase: 'Pomodoro 25 minutes focus',
+    expectedFields: ['duration', 'timerType'],
+    description: 'Pomodoro type',
+  },
+  {
+    phrase: 'Take meds at 8am, noon, and 8pm',
+    expectedFields: ['targetTime', 'recurrence'],
+    description: 'Multi-time alarm',
+  },
+  {
+    phrase: 'Boil eggs for 7 minutes',
+    expectedFields: ['duration', 'label'],
+    description: 'Labeled timer',
+  },
+  {
+    phrase: 'Set a 1 hour countdown',
+    expectedFields: ['duration'],
+    description: 'Explicit countdown',
+  },
+  {
+    phrase: 'Dentist appointment in 3 days',
+    expectedFields: ['targetTime'],
+    description: 'Days-ahead event',
+  },
+];
+
+// ── Types ──────────────────────────────────────────────────────────────────────
+
+type EvalOutcome = 'pass' | 'fail' | 'partial' | 'error';
+
+interface ParseEvalResult {
+  phrase: string;
+  description: string;
+  expectedFields: string[];
+  parsedFields: string[];
+  missingFields: string[];
+  outcome: EvalOutcome;
+  errorMessage?: string;
+  rawExtraction: unknown;
+}
+
+export interface NLParserEvalReport {
+  runId: string;
+  productId: 'chronomind';
+  totalCases: number;
+  passed: number;
+  partial: number;
+  failed: number;
+  errored: number;
+  passRate: number;
+  results: ParseEvalResult[];
+  regressions: string[];
+  summary: string;
+  generatedAt: string;
+}
+
+// ── Step 1: PhraseSamplerAgent ────────────────────────────────────────────────
+
+function assemblePhrases(customPhrases: string[]): NLTestCase[] {
+  const custom: NLTestCase[] = customPhrases.map(phrase => ({
+    phrase,
+    expectedFields: ['duration'],
+    description: 'Custom phrase',
+  }));
+  return [...CANONICAL_TEST_CASES, ...custom];
+}
+
+// ── Step 2: ParseEvalAgent ────────────────────────────────────────────────────
+
+async function evalPhrase(
+  testCase: NLTestCase,
+  opts: { token?: string; requestId?: string }
+): Promise<ParseEvalResult> {
+  try {
+    const result = await extractionRun({ text: testCase.phrase, taskId: 'timer-parse' }, opts);
+
+    // Extract field names from the extraction result
+    const parsedFields: string[] = [];
+    for (const item of result.extractions) {
+      const itemRecord = item as unknown as Record<string, unknown>;
+      const type = String(itemRecord['type'] ?? itemRecord['entity'] ?? '').toLowerCase();
+      if (type) parsedFields.push(type);
+      // Also check properties for known timer fields
+      const props = itemRecord['properties'] as Record<string, unknown> | undefined;
+      if (props) {
+        for (const key of ['duration', 'targetTime', 'timerType', 'recurrence', 'label']) {
+          if (key in props && !parsedFields.includes(key)) parsedFields.push(key);
+        }
+      }
+    }
+
+    const missingFields = testCase.expectedFields.filter(
+      f => !parsedFields.some(p => p.includes(f.toLowerCase()))
+    );
+    const outcome: EvalOutcome =
+      missingFields.length === 0
+        ? 'pass'
+        : missingFields.length < testCase.expectedFields.length
+          ? 'partial'
+          : 'fail';
+
+    return {
+      phrase: testCase.phrase,
+      description: testCase.description,
+      expectedFields: testCase.expectedFields,
+      parsedFields,
+      missingFields,
+      outcome,
+      rawExtraction: result.extractions,
+    };
+  } catch (err) {
+    return {
+      phrase: testCase.phrase,
+      description: testCase.description,
+      expectedFields: testCase.expectedFields,
+      parsedFields: [],
+      missingFields: testCase.expectedFields,
+      outcome: 'error',
+      errorMessage: err instanceof Error ? err.message : String(err),
+      rawExtraction: null,
+    };
+  }
+}
+
+// ── Step 3: RegressionReportAgent ─────────────────────────────────────────────
+
+function buildEvalReport(runId: string, results: ParseEvalResult[]): NLParserEvalReport {
+  const passed = results.filter(r => r.outcome === 'pass').length;
+  const partial = results.filter(r => r.outcome === 'partial').length;
+  const failed = results.filter(r => r.outcome === 'fail').length;
+  const errored = results.filter(r => r.outcome === 'error').length;
+  const passRate = results.length > 0 ? passed / results.length : 0;
+
+  const regressions = results
+    .filter(r => r.outcome === 'fail' || r.outcome === 'error')
+    .map(r => `"${r.phrase}" — missing: ${r.missingFields.join(', ') || r.errorMessage}`);
+
+  const summary =
+    results.length === 0
+      ? 'No test cases evaluated.'
+      : `${passed}/${results.length} passed (${(passRate * 100).toFixed(0)}%). ${partial} partial, ${failed} failed, ${errored} errored.${regressions.length > 0 ? ` Regressions: ${regressions.length}.` : ' No regressions detected.'}`;
+
+  return {
+    runId,
+    productId: 'chronomind',
+    totalCases: results.length,
+    passed,
+    partial,
+    failed,
+    errored,
+    passRate,
+    results,
+    regressions,
+    summary,
+    generatedAt: new Date().toISOString(),
+  };
+}
+
+// ── Pipeline runner ────────────────────────────────────────────────────────────
+
+async function runNLParserEvalPipeline(
+  customPhrases: string[],
+  req: McpToolRequest
+): Promise<NLParserEvalReport> {
+  const runId = randomUUID();
+  const opts = { token: req.headers.authorization?.slice(7), requestId: req.id };
+
+  req.log.info(
+    { runId, stepId: 'sample', customCount: customPhrases.length },
+    'PhraseSamplerAgent start'
+  );
+  const testCases = assemblePhrases(customPhrases);
+  req.log.info(
+    { runId, stepId: 'sample', totalCases: testCases.length },
+    'PhraseSamplerAgent done'
+  );
+
+  req.log.info({ runId, stepId: 'eval', totalCases: testCases.length }, 'ParseEvalAgent start');
+  const results: ParseEvalResult[] = [];
+  for (const testCase of testCases) {
+    const result = await evalPhrase(testCase, opts);
+    results.push(result);
+  }
+  const passed = results.filter(r => r.outcome === 'pass').length;
+  req.log.info({ runId, stepId: 'eval', passed, total: results.length }, 'ParseEvalAgent done');
+
+  req.log.info({ runId, stepId: 'report' }, 'RegressionReportAgent start');
+  const report = buildEvalReport(runId, results);
+  req.log.info(
+    { runId, stepId: 'report', passRate: report.passRate, regressions: report.regressions.length },
+    'RegressionReportAgent done'
+  );
+
+  return report;
+}
+
+// ── MCP tool registration ─────────────────────────────────────────────────────
+
+registerTool({
+  name: 'chronomind.nlParser.eval',
+  description:
+    'A2A pipeline: evaluates the ChronoMind natural-language timer parser by submitting a canonical phrase test suite (plus optional custom phrases) to the extraction service timer-parse task, validates parsed fields, and produces a pass/fail regression scorecard. Run after nl-parser changes to detect regressions. Requires admin role.',
+  requiredRole: 'admin',
+  inputSchema: z.object({
+    customPhrases: z
+      .array(z.string().min(1))
+      .default([])
+      .describe('Additional phrases to test beyond the built-in canonical suite'),
+  }),
+  async execute(args, req) {
+    return runNLParserEvalPipeline(args.customPhrases, req);
+  },
+});
diff --git a/services/mcp-server/src/modules/a2a/reflection-synthesis-pipeline.ts b/services/mcp-server/src/modules/a2a/reflection-synthesis-pipeline.ts
new file mode 100644
index 00000000..cde896f6
--- /dev/null
+++ b/services/mcp-server/src/modules/a2a/reflection-synthesis-pipeline.ts
@@ -0,0 +1,203 @@
+/**
+ * ReflectionSynthesisAgent — A2A pipeline for MindLyst weekly reflection synthesis.
+ *
+ * Agent roster (3 steps):
+ *   1. ReflectionCollectorAgent  — fetch recent reflections
+ *   2. ThemeExtractionAgent      — run reflection-enrichment extraction on concatenated reflection text
+ *   3. SynthesisReportAgent      — surface recurring themes, propose weekly summary text
+ *
+ * MCP tools:
+ *   mindlyst.reflections.synthesize(limit?) — run pipeline
+ */
+
+import { randomUUID } from 'node:crypto';
+import { z } from 'zod';
+import { registerTool } from '../tools/registry.js';
+import type { McpToolRequest } from '../tools/types.js';
+import { mindlystReflectionsList, type ReflectionDoc } from '../../lib/mindlyst-client.js';
+import { extractionRun, type ExtractionItem } from '../../lib/extraction-client.js';
+
+// ── Types ──────────────────────────────────────────────────────────────────────
+
+interface ThemeFrequency {
+  theme: string;
+  occurrences: number;
+  sources: string[];
+}
+
+export interface ReflectionSynthesisReport {
+  runId: string;
+  productId: 'mindlyst';
+  reflectionsAnalyzed: number;
+  topThemes: ThemeFrequency[];
+  highlights: string[];
+  challenges: string[];
+  extractedEntities: ExtractionItem[];
+  proposedSummary: string;
+  generatedAt: string;
+}
+
+// ── Step 1: ReflectionCollectorAgent ──────────────────────────────────────────
+
+async function collectReflections(
+  limit: number,
+  opts: { token?: string; requestId?: string }
+): Promise<ReflectionDoc[]> {
+  try {
+    const result = await mindlystReflectionsList({ limit }, opts);
+    return result.items;
+  } catch {
+    return [];
+  }
+}
+
+// ── Step 2: ThemeExtractionAgent ──────────────────────────────────────────────
+
+async function extractThemes(
+  reflections: ReflectionDoc[],
+  opts: { token?: string; requestId?: string }
+): Promise<{ entities: ExtractionItem[]; rawText: string }> {
+  if (reflections.length === 0) return { entities: [], rawText: '' };
+
+  const allThemes = reflections.flatMap(r => r.themes);
+  const allHighlights = reflections.flatMap(r => r.highlights);
+  const allChallenges = reflections.flatMap(r => r.challenges);
+  const summaries = reflections.map(r => r.summary).filter(Boolean) as string[];
+
+  const rawText = [
+    'Themes: ' + allThemes.join(', '),
+    'Highlights: ' + allHighlights.join('. '),
+    'Challenges: ' + allChallenges.join('. '),
+    summaries.length > 0 ? 'Summaries: ' + summaries.join(' ') : '',
+  ]
+    .filter(Boolean)
+    .join('\n');
+
+  try {
+    const result = await extractionRun({ text: rawText, taskId: 'reflection-enrichment' }, opts);
+    return { entities: result.extractions, rawText };
+  } catch {
+    return { entities: [], rawText };
+  }
+}
+
+// ── Step 3: SynthesisReportAgent ──────────────────────────────────────────────
+
+function buildThemeFrequencies(reflections: ReflectionDoc[]): ThemeFrequency[] {
+  const frequencyMap = new Map<string, { count: number; sources: string[] }>();
+
+  for (const reflection of reflections) {
+    for (const theme of reflection.themes) {
+      const entry = frequencyMap.get(theme) ?? { count: 0, sources: [] };
+      entry.count++;
+      entry.sources.push(reflection.weekStartDate);
+      frequencyMap.set(theme, entry);
+    }
+  }
+
+  return Array.from(frequencyMap.entries())
+    .map(([theme, { count, sources }]) => ({ theme, occurrences: count, sources }))
+    .sort((a, b) => b.occurrences - a.occurrences)
+    .slice(0, 10);
+}
+
+function buildProposedSummary(
+  topThemes: ThemeFrequency[],
+  highlights: string[],
+  challenges: string[],
+  reflectionCount: number
+): string {
+  if (reflectionCount === 0) return 'No reflections found to synthesize.';
+
+  const topThemeNames = topThemes
+    .slice(0, 3)
+    .map(t => t.theme)
+    .join(', ');
+  const summaryParts: string[] = [
+    `Across ${reflectionCount} reflection(s), recurring themes include: ${topThemeNames || 'none identified'}.`,
+  ];
+  if (highlights.length > 0) {
+    summaryParts.push(`Key highlights: ${highlights.slice(0, 3).join('; ')}.`);
+  }
+  if (challenges.length > 0) {
+    summaryParts.push(`Challenges to address: ${challenges.slice(0, 2).join('; ')}.`);
+  }
+  return summaryParts.join(' ');
+}
+
+// ── Pipeline runner ────────────────────────────────────────────────────────────
+
+async function runReflectionSynthesisPipeline(
+  limit: number,
+  req: McpToolRequest
+): Promise<ReflectionSynthesisReport> {
+  const runId = randomUUID();
+  const opts = { token: req.headers.authorization?.slice(7), requestId: req.id };
+
+  req.log.info({ runId, stepId: 'collect', limit }, 'ReflectionCollectorAgent start');
+  const reflections = await collectReflections(limit, opts);
+  req.log.info(
+    { runId, stepId: 'collect', count: reflections.length },
+    'ReflectionCollectorAgent done'
+  );
+
+  req.log.info(
+    { runId, stepId: 'extract', count: reflections.length },
+    'ThemeExtractionAgent start'
+  );
+  const { entities } = await extractThemes(reflections, opts);
+  req.log.info(
+    { runId, stepId: 'extract', entityCount: entities.length },
+    'ThemeExtractionAgent done'
+  );
+
+  req.log.info({ runId, stepId: 'synthesize' }, 'SynthesisReportAgent start');
+  const topThemes = buildThemeFrequencies(reflections);
+  const allHighlights = reflections.flatMap(r => r.highlights);
+  const allChallenges = reflections.flatMap(r => r.challenges);
+  const proposedSummary = buildProposedSummary(
+    topThemes,
+    allHighlights,
+    allChallenges,
+    reflections.length
+  );
+
+  const report: ReflectionSynthesisReport = {
+    runId,
+    productId: 'mindlyst',
+    reflectionsAnalyzed: reflections.length,
+    topThemes,
+    highlights: allHighlights,
+    challenges: allChallenges,
+    extractedEntities: entities,
+    proposedSummary,
+    generatedAt: new Date().toISOString(),
+  };
+  req.log.info(
+    { runId, stepId: 'synthesize', themeCount: topThemes.length },
+    'SynthesisReportAgent done'
+  );
+
+  return report;
+}
+
+// ── MCP tool registration ─────────────────────────────────────────────────────
+
+registerTool({
+  name: 'mindlyst.reflections.synthesize',
+  description:
+    'A2A pipeline: collects recent MindLyst reflections, runs reflection-enrichment extraction to surface entities and patterns, identifies recurring themes, and proposes a weekly summary text. Returns top themes by frequency, extracted entities, and a draft weekly summary. Requires admin role.',
+  requiredRole: 'admin',
+  inputSchema: z.object({
+    limit: z.coerce
+      .number()
+      .int()
+      .min(1)
+      .max(52)
+      .default(8)
+      .describe('Number of recent reflections to include (default 8, max 52 = 1 year)'),
+  }),
+  async execute(args, req) {
+    return runReflectionSynthesisPipeline(args.limit, req);
+  },
+});
diff --git a/services/mcp-server/src/server.ts b/services/mcp-server/src/server.ts
index ab51590e..9d17827a 100644
--- a/services/mcp-server/src/server.ts
+++ b/services/mcp-server/src/server.ts
@@ -48,6 +48,9 @@ import './modules/a2a/triage-quality-pipeline.js';
 import './modules/a2a/stt-fallback-monitor-pipeline.js';
 import './modules/a2a/progress-analyst-pipeline.js';
 import './modules/a2a/brain-overflow-pipeline.js';
+import './modules/a2a/reflection-synthesis-pipeline.js';
+import './modules/a2a/keyboard-diagnostics-pipeline.js';
+import './modules/a2a/nl-parser-eval-pipeline.js';
 import './modules/mindlyst/mindlyst-tools.js';
 import './modules/lysnrai/lysnrai-tools.js';
 import './modules/jarvis/jarvis-tools.js';