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AegisFlow代理治理系统
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AegisFlow代理治理系统

基于 Go · 让 AI 助手直接操作你的系统与工具
英文名:AegisFlow
⭐ 20 Stars 🍴 9 Forks 💻 Go 📄 Apache-2.0 🏷 AI 7.8分
7.8AI 综合评分
代理治理MCP工具编码代理安全控制GitHub集成
✦ AI Skill Hub 推荐

AI Skill Hub 推荐使用:AegisFlow代理治理系统 是一款优质的MCP工具。AI 综合评分 7.8 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。

📚 深度解析

AegisFlow代理治理系统 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 AegisFlow代理治理系统,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。AegisFlow代理治理系统 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 AegisFlow代理治理系统 评为 AI 评分 7.8 分,属于同类工具中的优质选择。

📋 工具概览

AegisFlow代理治理系统 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 20
开发语言
Go
支持平台
Windows / macOS / Linux(跨平台)
维护状态
轻量级项目,按需更新
开源协议
Apache-2.0
AI 综合评分
7.8 分
工具类型
MCP工具
Forks
9

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

AegisFlow代理治理系统 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/saivedant169/AegisFlow

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "aegisflow------": {
      "command": "npx",
      "args": ["-y", "aegisflow"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 AegisFlow代理治理系统 执行以下任务...
Claude: [自动调用 AegisFlow代理治理系统 MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "aegisflow______": {
      "command": "npx",
      "args": ["-y", "aegisflow"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 81/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

简介

<p align="center"> <h1 align="center">AegisFlow</h1> <p align="center"> <strong>Local-first runtime governance for coding agents and tool-using agents</strong> </p> <p align="center"> Let agents read, test, edit, and open PRs safely. Block destructive actions,<br/> review risky writes, mint short-lived credentials, and verify tamper-evident evidence. </p> <p align="center"> <a href="#start-here-governed-pr-writer">Start Here</a> | <a href="#what-aegisflow-controls">What It Controls</a> | <a href="#how-it-works">How It Works</a> | <a href="#design-principles">Design Principles</a> | <a href="#legacy--supporting-capabilities">Gateway Mode</a> | <a href="#contributing">Contributing</a> </p> </p>

---

CI Go Report Card Go Reference License Docker

Start here: See the governed PR-writer walkthrough with blocked shell actions, reviewed GitHub writes, scoped credentials, and verifiable evidence. → docs/PR_WRITER.md

Legacy / Supporting Capabilities

The sections below cover gateway mode — AegisFlow's earlier identity as an OpenAI-compatible AI gateway with policy, observability, and mock provider. Gateway mode is still fully supported and is what powers the governance plane internally, but the primary product story is governed agent execution above. If you arrived here looking for an AI gateway, this is the right place.

Features

Install without building from source

Grab a prebuilt binary (no Go toolchain needed):

curl -fsSL https://raw.githubusercontent.com/saivedant169/AegisFlow/main/scripts/install.sh | sh

Or run the published container:

docker run --rm -p 8080:8080 -p 8081:8081 \
  -v "$PWD/configs/aegisflow.yaml:/app/configs/aegisflow.yaml" \
  saivedant169/aegisflow:v0.8.0

Building from source still works (make build, Go 1.26.4+) if you prefer.

---

Option 1: Docker Compose

git clone https://github.com/saivedant169/AegisFlow.git
cd AegisFlow
docker compose -f deployments/docker-compose.yaml up

Putting nginx or Caddy in front for TLS, SSE buffering, and admin-port isolation: see docs/deploy/reverse-proxy.md. Hit a snag? docs/troubleshooting.md covers port conflicts, Docker daemon issues, GitHub App config, invalid policy files, and evidence-verify failures.

Install Go 1.26.4+

brew install go

Clone and build

git clone https://github.com/saivedant169/AegisFlow.git cd AegisFlow make build

Cost-free examples

The examples directory includes local-only configs and requests:

  • examples/configs/single-tenant.yaml
  • examples/configs/multi-tenant.yaml
  • examples/configs/policy-blocking.yaml
  • examples/requests/openai-compatible-curl.sh

Run an example config:

make build
./bin/aegisflow --config examples/configs/single-tenant.yaml
./examples/requests/openai-compatible-curl.sh

One-click gateway demo

git clone https://github.com/saivedant169/AegisFlow.git
cd AegisFlow
make demo-local

Run the governance demo

```bash

In another terminal, run the interactive demo

./scripts/demo.sh


The demo walks through the full agent governance flow: allowed reads, blocked
destructive operations, human-in-the-loop approval for writes, and evidence
chain verification. See [`configs/demo.yaml`](configs/demo.yaml) for the
policy configuration and [`scripts/demo.sh`](scripts/demo.sh) for the script.

To run with Docker instead:
bash docker compose -f deployments/docker-compose.demo.yaml up --build ```

Run the interactive demo

./scripts/realworld_demo.sh ```

The demo sends MCP tool calls through AegisFlow and demonstrates: - Allowed reads: github.list_repos, github.list_pull_requests pass through - Review required: github.create_pull_request enters the approval queue - Blocked destructive ops: github.delete_repo is rejected - Evidence chain: all decisions are recorded and verifiable

See configs/realworld.yaml for the policy configuration, scripts/mock-mcp-server.js for the mock server, and scripts/realworld_demo.sh for the full test script.

---

The core object: ActionEnvelope

Every agent action is normalized into an ActionEnvelope:

type ActionEnvelope struct {
    ID                string            // unique action ID
    Actor             ActorInfo         // who: user, agent, session
    Task              string            // declared task or ticket
    Protocol          string            // MCP, HTTP, shell, SQL, Git
    Tool              string            // github.create_pull_request, shell.exec
    Target            string            // repo, host, table, service
    Parameters        map[string]any    // normalized arguments
    RequestedCapability string          // read, write, delete, deploy, approve
    CredentialRef     string            // to-be-issued or attached
    PolicyDecision    string            // allow, review, block
    EvidenceHash      string            // chain pointer
    Justification     string            // model explanation, approval, policy match
}

---

Option 2: Run locally

```bash

Run with default config

make run ```

Start AegisFlow with demo config

make run CONFIG=configs/demo.yaml

Configuration

AegisFlow is configured via a single YAML file. See configs/aegisflow.example.yaml for the full annotated reference.

Minimal config

server:
  port: 8080
  admin_port: 8081

providers:
  - name: "mock"
    type: "mock"
    enabled: true
    default: true

tenants:
  - id: "default"
    api_keys: ["my-api-key"]
    rate_limit:
      requests_per_minute: 60
      tokens_per_minute: 100000

routes:
  - match:
      model: "*"
    providers: ["mock"]
    strategy: "priority"

Policy configuration

policies:
  input:
    - name: "block-jailbreak"
      type: "keyword"
      action: "block"
      keywords:
        - "ignore previous instructions"
        - "ignore all instructions"
        - "DAN mode"
    - name: "pii-detection"
      type: "pii"
      action: "warn"
      patterns: ["ssn", "email", "credit_card"]
  output:
    - name: "content-filter"
      type: "keyword"
      action: "log"
      keywords: ["harmful-keyword"]

Multi-provider config with fallback

providers:
  - name: "openai"
    type: "openai"
    enabled: true
    base_url: "https://api.openai.com/v1"
    api_key_env: "OPENAI_API_KEY"
    models: ["openai-chat", "openai-fast"]

  - name: "anthropic"
    type: "anthropic"
    enabled: true
    base_url: "https://api.anthropic.com/v1"
    api_key_env: "ANTHROPIC_API_KEY"
    models: ["claude-sonnet-4-20250514"]

routes:
  - match:
      model: "openai-*"
    providers: ["openai", "mock"]
    strategy: "priority"

  - match:
      model: "claude-*"
    providers: ["anthropic", "mock"]
    strategy: "priority"

---

Adoption

  • [x] Phase 9: Governed Coding Agent Starter Kit (3 policy packs, editor configs, Docker/Helm/Terraform deploy templates, efficacy tests, evidence examples)
  • [x] Phase 10: PR-writer proof page, focused installer, tuned policy pack, design-partner onboarding

---

API Reference

Gateway API (port 8080)

MethodEndpointDescription
GET/healthHealth check
POST/v1/chat/completionsChat completion (streaming and non-streaming)
GET/v1/modelsList available models
WS/v1/wsWebSocket endpoint for persistent connections

Admin API (port 8081)

MethodEndpointDescription
GET/healthAdmin health check
GET/metricsPrometheus metrics
GET/admin/v1/usageUsage statistics per tenant
GET/admin/v1/providersProvider status and health
GET/admin/v1/tenantsTenant configuration summary
GET/admin/v1/policiesActive policy rules
GET/admin/v1/whoamiCurrent API key role and tenant
GET/admin/v1/analyticsReal-time analytics summary
GET/admin/v1/alertsRecent anomaly alerts
POST/admin/v1/alerts/{id}/acknowledgeAcknowledge alert
GET/admin/v1/budgetsBudget statuses and forecasts
GET/admin/v1/cost-recommendationsCost optimization recommendations
GET/admin/v1/auditQuery audit log (filter by actor, action, tenant)
POST/admin/v1/audit/verifyVerify audit chain integrity
POST/admin/v1/graphqlGraphQL admin API
GET/admin/v1/approvalsList pending approvals
POST/admin/v1/approvals/{id}/approveApprove action
POST/admin/v1/approvals/{id}/denyDeny action
GET/admin/v1/evidence/sessionsList evidence sessions
GET/admin/v1/evidence/sessions/{id}/exportExport session evidence (JSON)
GET/admin/v1/evidence/sessions/{id}/reportHuman-readable Markdown report
GET/admin/v1/evidence/sessions/{id}/report.htmlHTML evidence report
POST/admin/v1/evidence/sessions/{id}/verifyVerify session chain integrity
GET/admin/v1/credentialsList active credentials
POST/admin/v1/credentials/{id}/revokeRevoke a credential
GET/admin/v1/manifestsList active task manifests
POST/admin/v1/manifestsCreate task manifest
GET/admin/v1/manifests/{id}/driftGet drift events for manifest
GET/admin/v1/ticketsList capability tickets
GET/admin/v1/sessions/{id}/riskSession behavioral risk score
POST/admin/v1/test-actionTest policy decision without executing
POST/admin/v1/simulateSimulate policy with full trace
GET/admin/v1/rolloutsList canary rollouts
GET/admin/v1/health/detailedDetailed health with provider status
GET/admin/v1/supply-chainSupply chain asset trust status

---

Runtime Integration

  • [x] Approval notifications: Slack + GitHub notifiers fire automatically on submit/approve/deny
  • [x] Behavioral kill switch: Sessions auto-blocked when cumulative risk exceeds threshold
  • [x] Manifest drift enforcement: Configurable warn/enforce mode blocks out-of-scope actions
  • [x] Evidence reports: Human-readable Markdown and HTML reports for auditors
🎯 aiskill88 AI 点评 B 级 2026-06-10

创新的代理治理方案,填补AI安全管理空白。Go实现性能优异,MCP标准兼容性强,但生态成熟度有限,适合前沿探索者。

⚡ 核心功能

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +Apache-2.0 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。

🔗 相关工具推荐

🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

通过MCP协议拦截代理操作,提供实时审查和阻止机制,支持自定义策略。
💡 AI Skill Hub 点评

总体来看,AegisFlow代理治理系统 是一款质量良好的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ Apache-2.0 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 AegisFlow代理治理系统
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 AegisFlow
原始描述 开源MCP工具:Runtime governance for coding agents and tool-using agents. Allow/review/block M。⭐20 · Go
Topics 代理治理MCP工具编码代理安全控制GitHub集成
GitHub https://github.com/saivedant169/AegisFlow
License Apache-2.0
语言 Go
🔗 原始来源
🐙 GitHub 仓库  https://github.com/saivedant169/AegisFlow 🌐 官方网站  https://github.com/saivedant169/AegisFlow/blob/main/docs/PR_WRITER.md

收录时间:2026-06-10 · 更新时间:2026-06-11 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。