Agentos

io.github.imran-siddique由 GitHub 账号 imran-siddique 发布v1.0.1更新于 Oct 24, 2026

Build and manage policy-compliant AI agents with safety enforcement and compliance checking

已验证STDIO仅桌面开发者工具安全与监控 AI 与机器学习

服务详情

标识符: io.github.imran-siddique/agentos
传输: STDIO
运行时: Desktop only
信任: Verified
发布于: Sep 16, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此条目所属的 GitHub 账号 imran-siddique。这并不表明该账号就是产品方。

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在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

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概览

AI 生成的概览

本地 MCP 服务器，用于创建、测试、部署和审计符合策略的 AI 智能体，内置安全策略与合规检查。

可以做什么: 智能体管理：根据自然语言描述创建智能体、附加安全策略、以试运行方式测试、部署到本地或云端，并查看状态与指标。策略：根据描述创建自定义策略，浏览内置策略与合规模板。审批：为敏感操作发起审批请求。审计与合规：查询审计记录，并按 SOC 2、GDPR、HIPAA、PCI DSS 等框架检查智能体。模板：浏览智能体与策略模板库。
适用场景: 适合希望让助手搭建带防护措施的自主智能体、在部署前做试运行测试，或为智能体工作流生成审计与合规报告的场景。若只需要一次简单的工具调用，则不太相关。
运行要求: 通过 stdio 在本地运行，通常使用 npx agentos-mcp-server，因此需要 Node.js。可选环境变量：AGENTOS_POLICY_MODE（strict 或 permissive）、AGENTOS_LOG_LEVEL、AGENTOS_DATA_DIR，以及用于云端功能的 AGENTOS_API_KEY。数据默认存储在本地数据目录。

安装前请注意

部署智能体会启动对真实数据（包括邮件、文件、数据库和云存储）执行操作的自动化，请先以试运行模式测试。permissive 策略模式仅对违规发出警告，strict 更安全。云端功能需要 AGENTOS_API_KEY。审计日志和智能体配置会写入本地数据目录。

安装

在 SourceWeft 中

打开控制台中的 Agentos，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Desktop only，通过 STDIO。 STDIO 服务会启动本地进程，因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照仓库中的启动说明。

README

AgentOS MCP Server

Build safe AI agents with natural language and 0% policy violations

[图片]

[npm version] [MCP Registry] [License: MIT]

Part of Agent OS - Kernel-level governance for AI agents

🚀 Quick Install

npm: agentos-mcp-server
MCP Registry: io.github.imran-siddique/agentos

Overview

AgentOS MCP Server brings the complete Agent OS safety framework to any MCP-compatible AI assistant including Claude Desktop, GitHub Copilot, Cursor, and more. Create, deploy, and manage policy-compliant autonomous agents through natural conversation.

┌─────────────────────────────────────────────────────────────┐│           Claude Desktop / Copilot / Cursor                  ││  ┌────────────────────────────────────────────────────────┐ ││  │            "Create an agent that..."                    │ ││  └──────────────────────┬─────────────────────────────────┘ │└─────────────────────────┼───────────────────────────────────┘                          │ MCP Protocol            ┌─────────────▼─────────────┐            │   🛡️ AgentOS MCP Server   │            │                           │            │  • 10 Tools              │            │  • Policy Engine         │            │  • Approval Workflows    │            │  • Audit Logging         │            │  • Template Library      │            └─────────────┬─────────────┘                          │      ┌───────────────────┼───────────────────┐      │                   │                   │┌─────▼─────┐      ┌──────▼──────┐     ┌─────▼─────┐│  Agents   │      │  Policies   │     │  Audit    ││  (Local)  │      │  (Enforced) │     │  (Logged) │└───────────┘      └─────────────┘     └───────────┘

┌─────────────────────────────────────────────────────────────┐│           Claude Desktop / Copilot / Cursor                  ││  ┌────────────────────────────────────────────────────────┐ ││  │            "Create an agent that..."                    │ ││  └──────────────────────┬─────────────────────────────────┘ │└─────────────────────────┼───────────────────────────────────┘                          │ MCP Protocol            ┌─────────────▼─────────────┐            │   🛡️ AgentOS MCP Server   │            │                           │            │  • 10 Tools              │            │  • Policy Engine         │            │  • Approval Workflows    │            │  • Audit Logging         │            │  • Template Library      │            └─────────────┬─────────────┘                          │      ┌───────────────────┼───────────────────┐      │                   │                   │┌─────▼─────┐      ┌──────▼──────┐     ┌─────▼─────┐│  Agents   │      │  Policies   │     │  Audit    ││  (Local)  │      │  (Enforced) │     │  (Logged) │└───────────┘      └─────────────┘     └───────────┘

✨ Features

🤖 Natural Language Agent Creation

User: Create an agent that processes customer feedback from support emails daily
Claude: ✅ Agent Created Successfully!
Agent: customer-feedback-processor✅ Data Source: Email inbox via IMAP✅ Processing: Sentiment analysis + categorization✅ Output: Daily summary to Slack✅ Schedule: Every day at 9 AM
Safety Policies Applied:🛡️ PII Protection: Customer emails/names anonymized🛡️ Rate Limiting: Max 1000 emails per run🛡️ Human Review: Negative sentiment cases flagged

User: Create an agent that processes customer feedback from support emails daily
Claude: ✅ Agent Created Successfully!
Agent: customer-feedback-processor✅ Data Source: Email inbox via IMAP✅ Processing: Sentiment analysis + categorization✅ Output: Daily summary to Slack✅ Schedule: Every day at 9 AM
Safety Policies Applied:🛡️ PII Protection: Customer emails/names anonymized🛡️ Rate Limiting: Max 1000 emails per run🛡️ Human Review: Negative sentiment cases flagged

🛡️ Policy Enforcement with 0% Violations

6 built-in policies (PII, rate-limiting, cost-control, data-deletion, secrets, human-review)
Real-time policy evaluation
Automatic blocking of violations
Clear explanations and alternatives

✅ Human-in-the-Loop Approval Workflows

Risk-based approval requirements
Multi-party approval for critical actions
Email/Slack notifications
Expiration handling

📊 Complete Audit Trail

Every action logged immutably
Policy evaluations recorded
Compliance report generation
Export for auditors

📋 Template Library

10+ agent templates (data processor, email assistant, backup, scraper, etc.)
6+ policy templates (GDPR, SOC 2, HIPAA, PCI DSS, etc.)
Industry-specific compliance frameworks

🏛️ Compliance Ready

SOC 2 - Security & availability controls
GDPR - EU data protection
HIPAA - Healthcare data privacy
PCI DSS - Payment card security
CCPA - California privacy
NIST - Cybersecurity framework
ISO 27001 - Information security
FedRAMP - Federal authorization

🚀 Quick Start

Step 1: Configure Claude Desktop

Add to your claude_desktop_config.json:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

json

{  "mcpServers": {    "agentos": {      "command": "npx",      "args": ["-y", "agentos-mcp-server"],      "env": {        "AGENTOS_POLICY_MODE": "strict"      }    }  }}

{  "mcpServers": {    "agentos": {      "command": "npx",      "args": ["-y", "agentos-mcp-server"],      "env": {        "AGENTOS_POLICY_MODE": "strict"      }    }  }}

Step 2: Restart Claude Desktop

Close and reopen Claude Desktop to load the MCP server.

Step 3: Start Building Agents!

Just ask Claude naturally:

Claude will:

Create the agent with appropriate configuration
Suggest safety policies based on the task
Let you test before deployment
Deploy with monitoring enabled

💬 Example Conversations

Creating a Data Processing Agent

User: I need an agent that processes customer feedback from support emails daily
Claude: ✅ Agent Created Successfully!
Agent: customer-feedback-processorID: a1b2c3d4-e5f6-7890-abcd-ef1234567890Status: draftLanguage: python
Task:Process customer feedback from support emails daily
Workflow Steps:1. connect_email: email.connect2. process_data: execute3. output_results: output
Safety Policies Applied:🛡️ PII Protection: Customer emails/names anonymized🛡️ Rate Limiting: Max 1000 emails per run🛡️ Human Review: Negative sentiment cases flagged
Next Steps:1. Use `test_agent` to run a dry-run test2. Use `attach_policy` to add more safety policies3. Use `deploy_agent` when ready to run

User: I need an agent that processes customer feedback from support emails daily
Claude: ✅ Agent Created Successfully!
Agent: customer-feedback-processorID: a1b2c3d4-e5f6-7890-abcd-ef1234567890Status: draftLanguage: python
Task:Process customer feedback from support emails daily
Workflow Steps:1. connect_email: email.connect2. process_data: execute3. output_results: output
Safety Policies Applied:🛡️ PII Protection: Customer emails/names anonymized🛡️ Rate Limiting: Max 1000 emails per run🛡️ Human Review: Negative sentiment cases flagged
Next Steps:1. Use `test_agent` to run a dry-run test2. Use `attach_policy` to add more safety policies3. Use `deploy_agent` when ready to run

Testing Before Deployment

User: Test this agent with a scenario of processing 100 emails
Claude: ✅ Test PASSED
Agent: customer-feedback-processorScenario: Process 100 customer emailsMode: Dry Run (no changes)
Configuration Check: ✅ ValidWorkflow Check: ✅ Valid (3 steps)
Policy Evaluation: ✅ No violations detected
Warnings:⚠️  PII access logged
Resource Estimates:- Duration: ~30 seconds- Cost: $0.05
Next Step: Use `deploy_agent` to deploy this agent.

User: Test this agent with a scenario of processing 100 emails
Claude: ✅ Test PASSED
Agent: customer-feedback-processorScenario: Process 100 customer emailsMode: Dry Run (no changes)
Configuration Check: ✅ ValidWorkflow Check: ✅ Valid (3 steps)
Policy Evaluation: ✅ No violations detected
Warnings:⚠️  PII access logged
Resource Estimates:- Duration: ~30 seconds- Cost: $0.05
Next Step: Use `deploy_agent` to deploy this agent.

Checking Compliance

User: Check if this agent is SOC 2 compliant
Claude: # Compliance Report: SOC2
Agent: customer-feedback-processorFramework: SOC2Date: 2026-01-30
## Summary✅ COMPLIANTScore: 100% (4/4 controls passed)
## Control Assessment
✅ CC6.1: Logical Access Controls   Restrict logical access to information assets   Evidence: Policy enforcement enabled, Access logging active
✅ CC6.6: Security Event Monitoring   Detect and respond to security events   Evidence: Audit logging enabled, Event timestamps recorded
✅ CC7.2: Incident Response   Respond to security incidents   Evidence: Human review enabled, Escalation procedures in place
✅ CC8.1: Change Management   Manage changes to system components   Evidence: Deployment approval required, Version control enabled

User: Check if this agent is SOC 2 compliant
Claude: # Compliance Report: SOC2
Agent: customer-feedback-processorFramework: SOC2Date: 2026-01-30
## Summary✅ COMPLIANTScore: 100% (4/4 controls passed)
## Control Assessment
✅ CC6.1: Logical Access Controls   Restrict logical access to information assets   Evidence: Policy enforcement enabled, Access logging active
✅ CC6.6: Security Event Monitoring   Detect and respond to security events   Evidence: Audit logging enabled, Event timestamps recorded
✅ CC7.2: Incident Response   Respond to security incidents   Evidence: Human review enabled, Escalation procedures in place
✅ CC8.1: Change Management   Manage changes to system components   Evidence: Deployment approval required, Version control enabled

Creating Custom Policies

User: Create a policy that blocks access to customer credit card data
Claude: ✅ Custom Policy Created
Policy: Block Access To CustomerID: custom-a1b2c3d4Category: security
Description:Block access to customer credit card data
Rules Generated (1):
🟠 custom_block_rule [high]   Block actions based on: block access to customer credit card data   Action: deny
Usage:1. Attach to agent: `attach_policy` with policyId "custom-a1b2c3d4"2. Test enforcement: `test_agent` with policy scenarios3. View active policies: `get_agent_status`

User: Create a policy that blocks access to customer credit card data
Claude: ✅ Custom Policy Created
Policy: Block Access To CustomerID: custom-a1b2c3d4Category: security
Description:Block access to customer credit card data
Rules Generated (1):
🟠 custom_block_rule [high]   Block actions based on: block access to customer credit card data   Action: deny
Usage:1. Attach to agent: `attach_policy` with policyId "custom-a1b2c3d4"2. Test enforcement: `test_agent` with policy scenarios3. View active policies: `get_agent_status`

🔧 Available Tools

Tool	Description
`create_agent`	Create agent from natural language description
`attach_policy`	Attach safety policies to agents
`test_agent`	Dry-run test before deployment
`deploy_agent`	Deploy agent locally or to cloud
`get_agent_status`	Get agent status and metrics
`list_templates`	Browse agent and policy templates
`request_approval`	Create approval request for sensitive actions
`audit_log`	Query audit trail
`create_policy`	Create custom policy from description
`check_compliance`	Check against compliance frameworks

Tool Details

`create_agent`

Create a new AI agent from a natural language description with automatic policy recommendations.

Parameters:

Parameter	Type	Required	Description
`description`	string	✅	Natural language description of agent task
`policies`	string[]		Policy templates to apply
`approvalRequired`	boolean		Require human approval before execution
`language`	string		`python`, `typescript`, `javascript`, `go`
`schedule`	string		Cron schedule for recurring execution

`attach_policy`

Attach safety policies to an agent with conflict detection.

Parameters:

`test_agent`

Run a dry-run test with simulated scenarios.

Parameters:

`deploy_agent`

Deploy an agent to local or cloud environment.

Parameters:

`check_compliance`

Check an agent against regulatory frameworks.

Parameters:

📋 Policy Templates

Built-in Security Policies

Policy ID	Name	Description
`pii-protection`	PII Protection	Protects personally identifiable information (GDPR)
`rate-limiting`	Rate Limiting	Prevents resource abuse through rate limits
`cost-control`	Cost Control	Prevents runaway costs from automation
`data-deletion`	Data Deletion Safety	Prevents accidental data loss
`secrets-protection`	Secrets Protection	Prevents exposure of credentials
`human-review`	Human Review Required	Requires approval for sensitive actions

Compliance Templates

Template ID	Framework	Description
`gdpr-compliance`	GDPR	EU General Data Protection Regulation
`soc2-security`	SOC 2	SOC 2 Type II security controls
`hipaa-healthcare`	HIPAA	Healthcare data privacy (PHI protection)
`pci-dss-payments`	PCI DSS	Payment card data security
`read-only-access`	Security	Restricts database to read-only
`production-safety`	Operations	Extra safeguards for production

🤖 Agent Templates

Data Processing

Template	Description	Default Policies
`data-processor`	Processes and transforms data files	rate-limiting, cost-control
`web-scraper`	Scrapes websites for data collection	rate-limiting, cost-control
`report-generator`	Generates periodic reports	pii-protection, rate-limiting

Communication

Infrastructure

Template	Description	Default Policies
`backup-agent`	Backs up files to cloud storage	cost-control
`api-monitor`	Monitors API health and performance	rate-limiting
`file-organizer`	Organizes files based on rules	data-deletion

Analytics

⚙️ Configuration

Environment Variables

Variable	Description	Default
`AGENTOS_API_KEY`	API key for cloud features	(none)
`AGENTOS_POLICY_MODE`	`strict` or `permissive`	`strict`
`AGENTOS_DATA_DIR`	Local data directory	`.agentos`
`AGENTOS_LOG_LEVEL`	`debug`, `info`, `warn`, `error`	`info`

Policy Modes

Data Storage

All data is stored locally in the AGENTOS_DATA_DIR:

.agentos/├── agents/           # Agent configurations│   └── {id}.json├── approvals/        # Approval requests│   └── {id}.json└── audit/            # Audit logs (JSONL format)    └── {date}.jsonl

.agentos/├── agents/           # Agent configurations│   └── {id}.json├── approvals/        # Approval requests│   └── {id}.json└── audit/            # Audit logs (JSONL format)    └── {date}.jsonl

🏗️ Architecture

┌─────────────────────────────────────────────────────────────┐│                     Claude Desktop                           ││  ┌────────────────────────────────────────────────────────┐ ││  │                    Claude AI Model                      │ ││  │     Natural language understanding & orchestration      │ ││  └──────────────────────┬─────────────────────────────────┘ ││                         │ MCP Protocol                       ││  ┌──────────────────────▼─────────────────────────────────┐ ││  │                    MCP Client                           │ ││  │          Tool discovery & request handling              │ ││  └──────────────────────┬─────────────────────────────────┘ │└─────────────────────────┼───────────────────────────────────┘                          │ stdio┌─────────────────────────▼───────────────────────────────────┐│               @agentos/mcp-server (Node.js)                 ││  ┌────────────────────────────────────────────────────────┐ ││  │                    MCP Server                           │ ││  │            Tool/Resource/Prompt handlers                │ ││  └────────────────────────────────────────────────────────┘ ││  ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌───────────────┐  ││  │  Agent   │ │  Policy  │ │ Approval │ │    Audit      │  ││  │ Manager  │ │  Engine  │ │ Workflow │ │   Logger      │  ││  └──────────┘ └──────────┘ └──────────┘ └───────────────┘  ││  ┌────────────────────────────────────────────────────────┐ ││  │              Template Library (50+ templates)           │ ││  └────────────────────────────────────────────────────────┘ │└─────────────────────────────────────────────────────────────┘                          │ HTTPS (optional)┌─────────────────────────▼───────────────────────────────────┐│              AgentOS Cloud Platform (Future)                ││     • Persistent storage  • Multi-tenant  • Enterprise      │└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐│                     Claude Desktop                           ││  ┌────────────────────────────────────────────────────────┐ ││  │                    Claude AI Model                      │ ││  │     Natural language understanding & orchestration      │ ││  └──────────────────────┬─────────────────────────────────┘ ││                         │ MCP Protocol                       ││  ┌──────────────────────▼─────────────────────────────────┐ ││  │                    MCP Client                           │ ││  │          Tool discovery & request handling              │ ││  └──────────────────────┬─────────────────────────────────┘ │└─────────────────────────┼───────────────────────────────────┘                          │ stdio┌─────────────────────────▼───────────────────────────────────┐│               @agentos/mcp-server (Node.js)                 ││  ┌────────────────────────────────────────────────────────┐ ││  │                    MCP Server                           │ ││  │            Tool/Resource/Prompt handlers                │ ││  └────────────────────────────────────────────────────────┘ ││  ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌───────────────┐  ││  │  Agent   │ │  Policy  │ │ Approval │ │    Audit      │  ││  │ Manager  │ │  Engine  │ │ Workflow │ │   Logger      │  ││  └──────────┘ └──────────┘ └──────────┘ └───────────────┘  ││  ┌────────────────────────────────────────────────────────┐ ││  │              Template Library (50+ templates)           │ ││  └────────────────────────────────────────────────────────┘ │└─────────────────────────────────────────────────────────────┘                          │ HTTPS (optional)┌─────────────────────────▼───────────────────────────────────┐│              AgentOS Cloud Platform (Future)                ││     • Persistent storage  • Multi-tenant  • Enterprise      │└─────────────────────────────────────────────────────────────┘

🔒 Security

Feature	Description
Policy Enforcement	All actions validated against policies before execution
Data Redaction	Sensitive data automatically redacted from logs
Secret Protection	Secrets never stored in plain text
Audit Trail	Complete immutable log for compliance
Human Approval	Required for high-risk operations
Local-First	All data stored locally by default

💻 Development

Local Development

bash

# Clone the repositorygit clone https://github.com/imran-siddique/agent-oscd agent-os/packages/mcp-server
# Install dependenciesnpm install
# Buildnpm run build
# Run in stdio mode (for Claude Desktop)npm start -- --stdio
# Run in HTTP mode (for development)npm start -- --http --port 3000

# Clone the repositorygit clone https://github.com/imran-siddique/agent-oscd agent-os/packages/mcp-server
# Install dependenciesnpm install
# Buildnpm run build
# Run in stdio mode (for Claude Desktop)npm start -- --stdio
# Run in HTTP mode (for development)npm start -- --http --port 3000

Project Structure

packages/mcp-server/├── src/│   ├── index.ts              # Main entry point│   ├── cli.ts                # CLI with --stdio/--http modes│   ├── server.ts             # MCP server implementation│   ├── tools/                # 10 MCP tools│   │   ├── create-agent.ts│   │   ├── attach-policy.ts│   │   ├── test-agent.ts│   │   ├── deploy-agent.ts│   │   ├── get-agent-status.ts│   │   ├── list-templates.ts│   │   ├── request-approval.ts│   │   ├── audit-log.ts│   │   ├── create-policy.ts│   │   └── check-compliance.ts│   ├── services/             # Core business logic│   │   ├── agent-manager.ts│   │   ├── policy-engine.ts│   │   ├── approval-workflow.ts│   │   ├── audit-logger.ts│   │   └── template-library.ts│   ├── prompts/              # MCP prompts│   └── types/                # TypeScript definitions├── package.json├── tsconfig.json└── README.md

packages/mcp-server/├── src/│   ├── index.ts              # Main entry point│   ├── cli.ts                # CLI with --stdio/--http modes│   ├── server.ts             # MCP server implementation│   ├── tools/                # 10 MCP tools│   │   ├── create-agent.ts│   │   ├── attach-policy.ts│   │   ├── test-agent.ts│   │   ├── deploy-agent.ts│   │   ├── get-agent-status.ts│   │   ├── list-templates.ts│   │   ├── request-approval.ts│   │   ├── audit-log.ts│   │   ├── create-policy.ts│   │   └── check-compliance.ts│   ├── services/             # Core business logic│   │   ├── agent-manager.ts│   │   ├── policy-engine.ts│   │   ├── approval-workflow.ts│   │   ├── audit-logger.ts│   │   └── template-library.ts│   ├── prompts/              # MCP prompts│   └── types/                # TypeScript definitions├── package.json├── tsconfig.json└── README.md

Running Tests

📊 Performance

📜 License

MIT License - see LICENSE.

Build safe AI agents with AgentOS

GitHub · Documentation · Report Issue

Made with 🛡️ by the Agent OS team

来源：extensions/mcp-server/README.md，提交 a7ee6eb

工具

SourceWeft 尚未在沙箱中启动过该软件包，因此其工具未知。

版本历史

v1.0.1最新Sep 16, 2026

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Template	Description	Default Policies
`email-assistant`	Monitors and processes emails	pii-protection, human-review
`slack-bot`	Automated Slack notifications	human-review, rate-limiting

Template	Description	Default Policies
`database-analyst`	Queries databases and generates reports	data-deletion, pii-protection
`content-moderator`	Moderates user-generated content	human-review, pii-protection

Metric	Target
MCP server startup	<2 seconds
Tool response time	<500ms (p95)
Memory footprint	<100MB
Policy evaluation	<50ms

Parameter	Type	Required	Description
`agentId`	string	✅	Agent ID to check
`framework`	string	✅	`SOC2`, `GDPR`, `HIPAA`, `PCI_DSS`, `CCPA`, `NIST`, `ISO27001`, `FEDRAMP`
`generateReport`	boolean		Generate detailed report

Mode	Behavior
strict	Any policy violation blocks the action
permissive	Only critical violations block (warnings logged)