evav-gateway

evav-gateway

Governed MCP gateway that lets AI agents call tools with policy enforcement, prompt-injection screening, a kill-switch, and tamper-evident signed audit logs.

Category
访问服务器

README

evav-gateway

The open-source governed MCP gateway. Point any AI agent (Claude, Cursor, ChatGPT, your own) at one endpoint; every tool call it makes is governed — policy-checked, screened for prompt-injection/exfiltration, haltable by a kill-switch — and written to a signed, tamper-evident audit log before it reaches the real tool.

Built on FastMCP for the wire (federation, pooled sessions, auth, transport); the governance layer is ours.

Status: v0.1, early. The governed proxy + signed audit + injection screening work and are tested. OAuth brokering, an OPA policy backend, the one-command client-setup, and packaging are on the roadmap below.

Why

Every OSS MCP gateway governs the wire. Most log unsigned, have no native injection screening, and no approval gate. evav-gateway:

  • Signs its audit log (Ed25519, hash-chained) — tamper-evident. No surveyed gateway does this.
  • Screens every call for prompt-injection / exfiltration on the way in and the way out — native, not a bolt-on.
  • Fails closed: a policy error, an injected argument, a poisoned upstream output, or an engaged kill-switch stops the call. It never silently allows.

Governance pipeline (per tool call)

kill-switch → policy (block / require-approval) → injection screen (input)
  → forward to upstream (pooled session) → injection screen (output, withhold)
  → signed audit record

Use as a library

from fastmcp import Client
from evav_gateway import build_gateway, Policy

gw, audit = build_gateway(
    {"mcpServers": {"slack": {"url": "https://mcp.slack.com/mcp"}}},
    policy=Policy(approval_tools=("payments.transfer",),
                  block_patterns=(r"\bssn\b",)),
)
# every call through `gw` is governed; audit.verify() checks the signed chain

Config-as-code

# evav-gateway.yaml
name: "Acme Gateway"
injection_on: true
upstreams:
  - name: slack
    url: https://mcp.slack.com/mcp
    auth_env: SLACK_MCP_TOKEN        # secret from env, never inlined
policy:
  approval_tools: [payments.transfer]
  block_patterns: ["\\bssn\\b", "password"]
  param_limits:
    payments.transfer: { amount: 1000 }
evav-gateway run --config evav-gateway.yaml

Quickstart

pip install evav-gateway          # or: uvx evav-gateway ...
cp evav-gateway.example.yaml evav-gateway.yaml     # edit upstreams + policy
evav-gateway run --config evav-gateway.yaml        # serves http://127.0.0.1:8000/mcp
evav-gateway client-setup --client cursor --url http://127.0.0.1:8000/mcp   # point your agent here

Or with Docker:

docker build -t evav-gateway .
docker run -p 8000:8000 -v "$PWD/evav-gateway.yaml:/config/evav-gateway.yaml" evav-gateway

Roadmap

  • [x] Governed proxy on FastMCP (policy · injection in/out · kill-switch · signed audit)
  • [x] evav-gateway client-setup — one command to point Claude/Cursor/VS Code/Windsurf here
  • [x] Docker image + uvx/pip install
  • [x] OPA (Rego) policy backend for enterprise param/context authz (opt-in; see examples/policy.rego)
  • [x] Brain-injection: inject the org's rules/skills into any agent (evav_rules / evav_skill)
  • [x] Persistent signed audit (SQLite + stable key) — retrieve via evav_audit, verify offline via evav-gateway verify-audit
  • [x] Hardened injection screen (decode pass: base64/URL/control-char obfuscation)
  • [ ] OAuth 2.1 + upstream token brokering (agents never hold upstream creds)
  • [ ] Shared multi-replica audit (Postgres + shared key)
  • [ ] Async endpoint + tuned connection pooling under load
  • [ ] Rule/skill/memory context injection (inject the org's relevant rules into any agent)
  • [ ] Helm chart

License

Apache-2.0.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选