开源MCP工具

Installation

npm install @blackms/aistack

Verify installation

npx @blackms/aistack status ```

Or install for your user (~/.claude/agents/), available in every project

npx @blackms/aistack export-agents --user

Example 2: Build Institutional Knowledge

Store patterns as you learn: ```bash

Build & Test

npm install               # Install dependencies
npm run build             # Build TypeScript to dist/
npm test                  # Run all tests (unit + integration)
npm run test:unit         # Unit tests only
npm run test:integration  # Integration tests only
npm run test:coverage     # Generate coverage report
npm run typecheck         # Type check without emit
npm run lint              # ESLint

Example workflow

You ask: "Create a login API endpoint with tests"

aistack:
1. Coder writes the endpoint
2. Tester creates and runs focused tests
3. Adversarial tries to break authentication and error paths
4. Coder fixes concrete findings
5. Reviewer gates the final patch
6. Memory stores the project pattern for future work

---

🚀 Quick Start

💡 Usage Examples

Example 1: Code Generation with Review

Via TypeScript:

import { createReviewLoop, getConfig } from '@blackms/aistack';

const result = await createReviewLoop(
  'Create REST API for user authentication',
  getConfig(),
  { maxIterations: 3 }
);

console.log(result.finalVerdict); // APPROVED or REJECTED
console.log(result.currentCode);  // Reviewed code after the final iteration
console.log(result.reviews);      // Concrete findings from each review round

Via REST/web API:

```bash

Example 3: Multi-Agent Collaboration

Generate feature with tests and docs:

import { spawnAgent, getMemoryManager, getConfig } from '@blackms/aistack';

// 1. Coder writes the feature
const coder = spawnAgent('coder', { name: 'feature-coder' });
const code = await executeTask(coder, 'Create user profile API');

// 2. Tester writes tests
const tester = spawnAgent('tester', { name: 'test-writer' });
const tests = await executeTask(tester, 'Write tests for user profile API');

// 3. Documentation agent generates docs
const docs = spawnAgent('documentation', { name: 'doc-writer' });
const documentation = await executeTask(docs, 'Document user profile API');

// 4. Store the pattern for future use
const memory = getMemoryManager(getConfig());
await memory.store('pattern:user-api', 'User API pattern with tests and docs', {
  namespace: 'patterns',
  metadata: { code, tests, documentation }
});

Example 4: Use in Claude Code

After installing the MCP server:

claude mcp add aistack -- npx @blackms/aistack mcp start

In Claude Code, you can:

"Spawn a researcher agent to analyze this codebase"
→ Uses agent_spawn tool

"Store this pattern in memory: Always validate user input"
→ Uses memory_store tool

"Search memory for authentication patterns"
→ Uses memory_search tool

"List all active agents"
→ Uses agent_list tool

Review loops are available through the TypeScript API (createReviewLoop) and REST/web API, not as MCP tools.

Example 5: CLI Workflow

```bash

Example 6: Web Dashboard

```bash

Configuration

Create aistack.config.json in your project root:

{
  "version": "1.5.3",
  "providers": {
    "default": "anthropic",
    "anthropic": {
      "apiKey": "${ANTHROPIC_API_KEY}",
      "model": "claude-sonnet-4-20250514"
    },
    "openai": {
      "apiKey": "${OPENAI_API_KEY}",
      "model": "gpt-4o"
    },
    "ollama": {
      "baseUrl": "http://localhost:11434",
      "model": "llama3.2"
    }
  },
  "memory": {
    "path": "./data/aistack.db",
    "vectorSearch": {
      "enabled": false,
      "provider": "openai"
    }
  },
  "driftDetection": {
    "enabled": false,
    "threshold": 0.95,
    "warningThreshold": 0.8,
    "ancestorDepth": 3,
    "behavior": "warn",
    "asyncEmbedding": true
  },
  "resourceExhaustion": {
    "enabled": false,
    "thresholds": {
      "maxFilesAccessed": 50,
      "maxApiCalls": 100,
      "maxSubtasksSpawned": 20,
      "maxTimeWithoutDeliverableMs": 1800000,
      "maxTokensConsumed": 500000
    },
    "warningThresholdPercent": 0.7,
    "checkIntervalMs": 10000,
    "autoTerminate": false,
    "requireConfirmationOnIntervention": true,
    "pauseOnIntervention": true
  },
  "slack": {
    "enabled": false,
    "webhookUrl": "${SLACK_WEBHOOK_URL}",
    "channel": "#aistack-notifications",
    "notifyOnAgentSpawn": false,
    "notifyOnWorkflowComplete": true,
    "notifyOnErrors": true,
    "notifyOnReviewLoop": true,
    "notifyOnResourceWarning": true,
    "notifyOnResourceIntervention": true
  },
  "consensus": {
    "enabled": false,
    "requireForRiskLevels": ["high", "medium"],
    "reviewerStrategy": "adversarial",
    "timeout": 300000,
    "maxDepth": 5,
    "autoReject": false,
    "highRiskAgentTypes": ["coder", "devops", "security-auditor"],
    "mediumRiskAgentTypes": ["architect", "coordinator", "analyst"],
    "highRiskPatterns": ["delete", "remove", "drop", "deploy", "production", "credentials", "secret", "password", "token", "api key"],
    "mediumRiskPatterns": ["modify", "update", "change", "configure", "install"]
  }
}

---

💻 Programmatic API

TypeScript SDK

import {
  spawnAgent,
  getMemoryManager,
  startMCPServer,
  getConfig,
  createReviewLoop,
} from '@blackms/aistack';

// Spawn an agent
const agent = spawnAgent('coder', {
  name: 'my-coder',
  metadata: { project: 'awesome-app' }
});

// Use memory with FTS5 search
const memory = getMemoryManager(getConfig());
await memory.store('architecture:pattern', 'Use dependency injection', {
  namespace: 'best-practices',
  tags: ['architecture', 'patterns'],
});

const results = await memory.search('dependency injection');
console.log(results); // FTS5 ranked results

// Start adversarial review loop
const reviewState = await createReviewLoop(
  'Write a secure authentication function',
  getConfig(),
  { maxIterations: 3 }
);

console.log(reviewState.finalVerdict); // APPROVED or REJECTED
console.log(reviewState.currentCode);
console.log(reviewState.reviews); // All review rounds

// Start MCP server
const server = await startMCPServer(getConfig());
console.log('MCP server listening on stdio');

📢 Slack Integration

Real-time notifications to your team: - Agent Events - Spawning, stopping, errors - Workflow Updates - Start, completion, failures - Review Loop Progress - Iteration updates - Resource Alerts - Warnings, interventions, terminations - Customizable - Choose which events to notify

---

Submodule Imports

import { MemoryManager } from '@blackms/aistack/memory';
import { spawnAgent, listAgentTypes, pauseAgent, resumeAgent } from '@blackms/aistack/agents';
import { startMCPServer } from '@blackms/aistack/mcp';
import { getResourceExhaustionService } from '@blackms/aistack/monitoring';

// Direct imports for smaller bundles
const agentTypes = listAgentTypes();
// => ['coder', 'researcher', 'tester', 'reviewer', 'adversarial', 'architect', 'coordinator', 'analyst', 'devops', 'documentation', 'security-auditor']

---

CI/CD Pipeline

GitHub Actions workflow with 5 parallel jobs:

1. Lint - ESLint code quality checks
2. Typecheck - TypeScript type validation
3. Unit Tests - Fast isolated tests
4. Integration Tests - Database + agent integration
5. Build - Production build verification

Code Coverage: Uploaded to Codecov after test completion

Code: .github/workflows/ci.yml

Comparison vs other agent orchestrators

Feature claims for third-party projects reflect public documentation at time of writing; PRs welcome to correct inaccuracies.

What is uniquely aistack: - Adversarial review loop as a first-class primitive — a dedicated agent attacks the coder's output up to N iterations until APPROVED. - Consensus checkpoints — high-risk task spawns can require human or different-model approval before proceeding, with full audit trail. - 46 MCP tools wired directly into Claude Code, including memory, identity, drift detection, and consensus management.

→ See docs/COMPARISON.md for the extended analysis including CrewAI, AutoGen, and Letta.

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