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name: using-apex-mcp description: Use when calling APEX MCP tools (apex_patterns_lookup, apex_patterns_overview, apex_task_create, apex_reflect, etc.) for pattern intelligence, task tracking, or submitting reflections. Reference guide for all 13 MCP tools with schemas, trust score interpretation (★ ratings), workflow integration, and common error fixes.

Using APEX MCP

APEX is an intelligent memory layer for AI coding assistants that provides pattern discovery, task intelligence, and continuous learning through 13 MCP (Model Context Protocol) tools.

Quick Reference

Tool	Purpose	When to Use
apex_patterns_lookup	Find relevant patterns by context	Starting any task, need proven solutions
apex_patterns_discover	Semantic pattern search	When lookup insufficient, exploring
apex_patterns_explain	Get pattern details	Deep dive on specific pattern
apex_patterns_overview	Browse/filter all patterns	Pattern management, exploring catalog
apex_task_create	Create task with auto-brief	Beginning any work
apex_task_find	Find tasks by criteria	Looking for similar past work
apex_task_find_similar	Get similar tasks	Need examples of similar implementations
apex_task_update	Track progress	Phase transitions, adding files/decisions
apex_task_checkpoint	Add progress note	Frequent progress tracking
apex_task_complete	Finish task (returns draft)	Work done, before reflection
apex_task_context	Get intelligence pack	After creating task, need patterns/similar tasks
apex_task_append_evidence	Add evidence	Tracking pattern usage, decisions
apex_reflect	Submit outcomes (complex!)	After completion, update pattern trust

Phase Model (Frontmatter vs Telemetry)

APEX uses two related phase concepts:

• Frontmatter phase (task file gating): research → plan → implement → rework → complete
• DB role/telemetry (MCP phase): RESEARCH → ARCHITECT → BUILDER → BUILDER_VALIDATOR → REVIEWER → DOCUMENTER

Legacy telemetry value VALIDATOR is still accepted for backward compatibility.

Trust Score Interpretation

Patterns include trust scores (0.0-1.0) that indicate reliability:

• ★★★★★ (0.9-1.0) - Apply confidently, proven patterns
• ★★★★☆ (0.7-0.9) - High trust, use with confidence
• ★★★☆☆ (0.5-0.7) - Moderate trust, apply with caution
• ★★☆☆☆ (0.3-0.5) - Low confidence, validate carefully
• ★☆☆☆☆ (0.0-0.3) - Untested or failing, avoid

Application Rule: Apply patterns with ★★★★☆+ (trust ≥ 0.7) confidently. Question patterns below ★★★☆☆ (trust < 0.5).

Typical Workflow

// 1. Create task
const task = await apex_task_create({
  intent: "Implement user authentication",
  type: "feature",
  tags: ["auth", "security", "api"]
})

// 2. Get intelligence (patterns + similar tasks)
const intel = await apex_task_context({
  task_id: task.id,
  packs: ["tasks", "patterns", "statistics"]
})

// 3. Discover specific patterns
const patterns = await apex_patterns_lookup({
  task: "JWT authentication with rate limiting",
  workflow_phase: "builder",  // architect|builder|validator|reviewer|documenter
  code_context: {
    current_file: "src/auth.ts",
    imports: ["jsonwebtoken"]
  }
})

// 4. Track progress through phases
await apex_task_update({
  id: task.id,
  phase: "BUILDER",  // RESEARCH→ARCHITECT→BUILDER→BUILDER_VALIDATOR→REVIEWER→DOCUMENTER (VALIDATOR is legacy)
  confidence: 0.75,
  files: ["src/auth.ts", "src/middleware/auth.ts"],
  handoff: "Architecture complete, implementing JWT auth"
})

// 5. Complete task (returns reflection draft - does NOT auto-submit)
const draft = await apex_task_complete({
  id: task.id,
  outcome: "success",  // success|partial|failure
  key_learning: "JWT auth with proper error handling saves 2 hours",
  patterns_used: ["PAT:AUTH:JWT", "FIX:ERROR:HANDLING"]
})

// 6. Submit reflection (MUST be explicit - updates pattern trust)
await apex_reflect(draft)  // Use the draft from apex_task_complete

Pattern Discovery Flow

Primary: Context-Aware Lookup

const patterns = await apex_patterns_lookup({
  task: "implement caching layer",
  task_intent: {
    type: "feature",
    confidence: 0.8
  },
  code_context: {
    current_file: "src/cache.ts",
    imports: ["redis", "ioredis"]
  },
  project_signals: {
    language: "typescript",
    framework: "express"
  }
})

// Returns: pattern_pack with trust-scored patterns
// Apply patterns with trust_score ≥ 0.7 confidently

Secondary: Semantic Search

const discovered = await apex_patterns_discover({
  query: "cache invalidation with TTL",
  filters: {
    min_trust: 0.7,  // Only high-trust patterns
    types: ["code", "pattern"]
  },
  max_results: 10
})

Deep Dive: Pattern Explanation

const details = await apex_patterns_explain({
  pattern_id: "PAT:CACHE:REDIS",
  verbosity: "detailed",  // concise|detailed|examples
  context: {
    task_type: "caching implementation"
  }
})

// Returns: explanation, when_to_use, how_to_apply, common_mistakes, examples

Task Tracking Pattern

Creating and Tracking

// Create with context
const task = await apex_task_create({
  intent: "Fix authentication timeout bug",
  type: "bug",
  identifier: "AUTH-TIMEOUT-123",  // External ID (e.g., JIRA)
  tags: ["auth", "bug", "timeout", "critical"]
})

// Get similar tasks for learning
const similar = await apex_task_find_similar({
  taskId: task.id
})

// Frequent checkpoints
await apex_task_checkpoint({
  id: task.id,
  message: "Identified root cause in session management",
  confidence: 0.6
})

// Append evidence for learning
await apex_task_append_evidence({
  task_id: task.id,
  type: "pattern",  // pattern|error|decision|learning|file
  content: "Applied PAT:SESSION:TIMEOUT for session expiry",
  metadata: {
    pattern_id: "PAT:SESSION:TIMEOUT",
    file: "src/session.ts",
    line_start: 45,
    line_end: 67
  }
})

Reflection Submission (CRITICAL)

⚠️ IMPORTANT: apex_reflect is the most complex tool with 20+ validation rules. See apex-reflect-guide.md for complete documentation.

Quick Guide

// STEP 1: Complete task (returns draft)
const draft = await apex_task_complete({
  id: task_id,
  outcome: "success",
  key_learning: "Pattern XYZ saved 2 hours",
  patterns_used: ["PAT:AUTH:JWT"]
})

// STEP 2: Commit changes FIRST (reflection validates git evidence)
await bash("git add . && git commit -m 'feat: implement auth'")

// STEP 3: Submit reflection (explicit call required)
await apex_reflect({
  task: { id: task_id, title: "Implement JWT auth" },
  outcome: "success",
  batch_patterns: [  // Simple format (RECOMMENDED)
    {
      pattern: "PAT:AUTH:JWT",
      outcome: "worked-perfectly",  // See valid outcomes below
      evidence: "Applied in src/auth.ts:45-78"
    }
  ]
})

Valid Pattern Outcomes

• "worked-perfectly" → 100% success (alpha: 1.0, beta: 0.0)
• "worked-with-tweaks" → 70% success (alpha: 0.7, beta: 0.3)
• "partial-success" → 50% success (alpha: 0.5, beta: 0.5)
• "failed-minor-issues" → 30% success (alpha: 0.3, beta: 0.7)
• "failed-completely" → 0% success (alpha: 0.0, beta: 1.0)

Common Reflection Errors

1. Using "code_lines" instead of "git_lines" → Auto-fixed by preprocessor
2. Missing SHA in git evidence → Auto-fixed to "HEAD"
3. Mixing claims and batch_patterns → Error: use ONE format only
4. Invalid outcome vocabulary → Use exact strings above
5. Not committing before reflection → Evidence validation fails

Quick Troubleshooting

Error: "InvalidParamsError"

• Check required fields (task, intent, id, etc.)
• Verify enum values (outcome, phase, type). phase accepts legacy values.
• Check length limits (task: 1-1000 chars, key_learning: 1-500 chars)

Error: "Pattern not found"

• In permissive mode (default): Pattern auto-created
• In strict mode: Error thrown
• Set mode: export APEX_REFLECTION_MODE=strict

Error: "Line range not found"

• Ensure lines exist at specified SHA
• Check file path is relative to repo root
• Verify git ref is valid (HEAD, main, SHA)

Error: "Duplicate trust update"

• Same pattern_id appears twice in trust_updates
• Consolidate to single update per pattern

Error: "Rate limit exceeded"

• Default: 100 requests per 60 seconds
• Configure via environment variables
• Use caching (5-minute TTL on lookup/discover)

Workflow Integration

APEX tools map to execution phases:

• RESEARCH: Use apex_task_create + apex_task_context to seed intelligence
• ARCHITECT: apex_patterns_lookup with workflow_phase: "architect", get architecture patterns
• BUILDER: apex_patterns_lookup with workflow_phase: "builder", implement with patterns, track via apex_task_update
• BUILDER_VALIDATOR: apex_patterns_lookup with workflow_phase: "validator", test/validate patterns
• VALIDATOR (legacy): accepted for older clients; prefer BUILDER_VALIDATOR going forward
• REVIEWER: Use apex_task_context to review journey, check patterns applied
• DOCUMENTER: apex_task_complete + apex_reflect to capture learnings

Advanced Features

Context Pack Structure

apex_task_context returns comprehensive intelligence:

• active_tasks: Tasks in progress
• recent_similar_tasks: Similar implementations with learnings
• task_statistics: Success rates, duration averages
• task_patterns: Common patterns by theme

Evidence Types (for apex_reflect)

• git_lines: File, SHA, line range (most common)
• commit: Git commit SHA
• pr: Pull request number and repo
• ci_run: CI run ID and provider

Batch vs Claims Format

Batch (simple, recommended):

batch_patterns: [{
  pattern: "PAT:ID",
  outcome: "worked-perfectly",
  notes: "Optional notes"
}]

Claims (advanced, full control):

claims: {
  patterns_used: [{
    pattern_id: "PAT:ID",
    evidence: [{ kind: "git_lines", file: "...", sha: "HEAD", start: 1, end: 10 }]
  }],
  trust_updates: [{ pattern_id: "PAT:ID", outcome: "worked-perfectly" }],
  new_patterns: [...],
  anti_patterns: [...],
  learnings: [...]
}

Additional Resources

• Complete Reflection Guide: See apex-reflect-guide.md for deep dive on apex_reflect with all validation rules, evidence types, and error handling
• Pattern Overview Guide: See apex-patterns-overview-guide.md for comprehensive guide on browsing and filtering patterns with apex_patterns_overview
• Tool Schemas: Full parameter documentation in MCP server source (src/mcp/tools/)
• Trust Calculation: Beta-Bernoulli model in src/trust/beta-bernoulli.ts

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Remember: APEX learns from your reflections. Submit outcomes via apex_reflect to improve pattern trust scores for future tasks.