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MCP Airlock

Name: MCP Airlock
Author: lara-muhanna

by lara-muhanna

Overview Schema Source Related Servers Discussions Admin

Python

Remote

MCP Airlock

License: MIT Python

MCP 도구를 위한 제로 트러스트 보안 게이트웨이. MCP Airlock은 모든 도구 호출을 변조 방지 출처가 포함된 단기적이고 컨텍스트에 바인딩된 권한 결정으로 전환합니다.

이 프로젝트의 존재 이유

에이전트 도구 생태계는 한 가지 고통스러운 경계에서 실패하고 있습니다: 신뢰할 수 없는 프롬프트 텍스트에서 권한이 부여된 도구 실행으로 넘어가는 단계입니다.

현재의 패턴은 대개 다음 중 하나입니다:

정적 허용 목록 (에이전트는 도구 X를 호출할 수 있음)
취약한 정규식 필터링
무결성 보장이 없는 사후 로그

이러한 방식은 프롬프트 주입이 세션 도중 의도를 변경하여 조용한 권한 상승이나 데이터 유출을 유발할 때 실패합니다.

MCP Airlock은 MCP에 누락된 기본 요소를 통해 이 문제를 해결합니다:

권한 임대(Capability Leases): 단기적이고 서명된 컨텍스트 바인딩 권한 (세션 + 의도 + 도구 범위 + 제약 조건)
컨텍스트 인식 정책: 모든 호출에 대한 동적 승인 (위험 점수 + 도구 제약 조건 + 임대 확인)
변조 방지 출처(Tamper-Evident Provenance): 모든 허용/거부 결정에 대한 추가 전용 해시 체인

Related MCP server: evav-gateway

핵심 혁신

컨텍스트 바인딩 권한 임대 (CBCL)

각 도구 호출은 서명된 임대에 대해 승인됩니다:

session_id에 바인딩됨
intent_hash에 바인딩됨
특정 도구로 범위가 제한됨
시간 제한 있음
선택적 제약 조건 (예: 허용된 도메인, 최대 위험도)

프롬프트 주입이 의도를 변경하거나 도구 범위를 벗어나려고 시도하면 실행이 거부됩니다.

아키텍처

flowchart LR
    A[Agent / MCP Client] -->|tools/call| B[MCP Airlock Server]
    B --> C[Risk Engine]
    B --> D[Capability Verifier]
    B --> E[Policy Engine]
    E -->|allow| F[Tool Adapter Layer]
    E -->|deny| G[Policy Deny Response]
    F --> H[External APIs / Internal Services]
    B --> I[Provenance Ledger Hash Chain]

신뢰 경계

flowchart TB
    subgraph Untrusted
      U1[Prompt Content]
      U2[Agent Reasoning Trace]
    end

    subgraph Trusted Control Plane
      T1[MCP Airlock]
      T2[Policy + Lease Validation]
      T3[Signed Provenance Ledger]
    end

    subgraph External Targets
      X1[Public APIs]
      X2[Internal APIs]
    end

    U1 --> T1
    U2 --> T1
    T1 --> T2
    T2 --> X1
    T2 --> X2
    T1 --> T3

주요 기능

initialize, tools/list, tools/call과 호환되는 MCP stdio 서버
권한 발급 도구: airlock_issue_capability
에이전트/API 사용량 분석 도구: airlock_usage_stats
API 노출 측정 도구: airlock_exposure_report
도구별 위험 임계값이 포함된 정책 시행 미들웨어
프롬프트 주입 서명 점수 산정
SSRF 방지 HTTP 도구 어댑터 (http_get_json)
실제 API 통합 예제 (weather_hourly)
변조 방지 출처 로그 + 검증 명령
에이전트 API 보안을 위한 샌드박스 강화 가이드
serve/demo/issue/verify/stats/exposure를 위한 CLI

2분 퀵스타트

git clone https://github.com/lara-muhanna/mcp-airlock
cd mcp-airlock
python -m pip install -e .
python -m mcp_airlock --config examples/airlock.config.json demo

확인할 수 있는 내용:

사람이 읽기 쉬운 요약 (핸드셰이크, 권한, 허용/거부, 감사 무결성)
악의적인 호출이 평이한 영어 이유와 함께 거부됨
서명된 출처 증거

한 줄 명령 로컬 데모 (설치 불필요)

python -m mcp_airlock --config examples/airlock.config.json demo --city Austin --state Texas

데모 중 전체 JSON 페이로드 확인:

python -m mcp_airlock --config examples/airlock.config.json demo --raw

MCP 서버로 실행

python -m mcp_airlock --config examples/airlock.config.json serve

MCP 클라이언트 설정 예제:

CLI

# Issue a capability directly
python -m mcp_airlock --config examples/airlock.config.json issue \
  --session-id sess-123 \
  --subject agent:planner \
  --tools weather_hourly,http_get_json \
  --intent "Plan safe outdoor activities" \
  --ttl-seconds 900 \
  --constraints '{"allowed_domains":["api.open-meteo.com"],"max_risk":0.6}'

# Verify audit integrity
python -m mcp_airlock --config examples/airlock.config.json verify-log

# API usage stats by agent
python -m mcp_airlock --config examples/airlock.config.json stats --lookback-hours 24

# API exposure measurement
python -m mcp_airlock --config examples/airlock.config.json exposure --lookback-hours 24

에이전트 통합 예제

실행:

python examples/agent_integration.py

이 스크립트는:

stdio를 통해 Airlock을 시작합니다
MCP initialize/list를 협상합니다
임대를 발급합니다
일반적인 도구 호출을 실행합니다
차단되는 주입된 호출을 실행합니다

설정 템플릿

examples/airlock.config.json

{
  "secret_key": "dev-secret-change-this-before-production",
  "provenance_log": "./airlock-provenance.log",
  "max_ttl_seconds": 1800,
  "default_risk_threshold": 0.55,
  "tools": {
    "weather_hourly": {
      "require_capability": true,
      "risk_threshold": 0.7
    },
    "http_get_json": {
      "require_capability": true,
      "risk_threshold": 0.45,
      "allowed_domains": ["api.open-meteo.com", "geocoding-api.open-meteo.com"]
    }
  }
}

보안 모델 요약

에이전트가 airlock_issue_capability를 통해 임대를 요청합니다.
임대는 HMAC 서명되며 session, intent_hash, tool_scope, expiry를 포함합니다.
모든 tools/call 요청은 _capability와 _context를 포함합니다.
Airlock은 다음을 시행합니다:
- 임대 유효성 + 서명
- 세션 및 의도 연속성
- 위험 임계값
- 도구별 제약 조건 (예: 도메인 허용 목록)
결정 + 증거는 출처 로그에 해시 체인으로 연결됩니다.

프로젝트 구조

mcp-airlock/
  mcp_airlock/
    cli.py
    server.py
    policy.py
    capability.py
    risk.py
    provenance.py
    config.py
    tool_ids.py
    tools/
      http_json.py
      weather.py
  examples/
    airlock.config.json
    agent_integration.py
  docs/
    CLIENT_SETUP.md
    SANDBOXING_AGENTIC_APIS.md

로드맵

업스트림 MCP 프록시 모드 (기존 MCP 서버를 투명하게 래핑)
OPA/Rego 정책 백엔드
OpenTelemetry 추적 + SIEM 싱크
관리형 권한 브로커 + 키 로테이션
사고 대응을 위한 서명된 리플레이 패키지

커뮤니티

기여 가이드: CONTRIBUTING.md
보안 정책: SECURITY.md
행동 강령: CODE_OF_CONDUCT.md
릴리스 체크리스트: docs/RELEASE_CHECKLIST.md

라이선스

MIT

Available Tools

4 tools

airlock_audit_tailC

Read recent signed provenance events.

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No

TDQS

C2.6/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it notes events are 'recent' and 'signed', it fails to specify the time window for 'recent', result ordering, return format, pagination behavior, or the implications of 'signed' (verification requirements?). This leaves critical behavioral gaps for an audit tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at five words, immediately front-loading the verb and object. While efficient, this brevity is arguably inappropriate given the complete absence of annotations and schema descriptions, leaving the description too terse to stand alone as documentation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a security/audit tool handling cryptographically signed provenance data, the description is inadequate. With no output schema, no parameter descriptions, and no annotations, the description should explain what data structure is returned and what 'airlock' provenance tracks, but it provides none of this context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage for the 'limit' parameter. The description completely fails to compensate by explaining the parameter's purpose, valid ranges, or default behavior (20). The agent has no textual guidance on how to use the only available parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Read') and the specific resource ('signed provenance events'), distinguishing it from the sibling 'airlock_issue_capability' (which issues/writes) and the unrelated 'weather_hourly' and 'http_get_json' tools. However, it could better clarify what constitutes a 'provenance event' in this specific 'airlock' domain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites (e.g., specific permissions needed to read signed audit trails) or when not to use it. The agent receives no signals about appropriate usage contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

airlock_issue_capabilityC

Issue a short-lived capability lease bound to session+intent.

ParametersJSON Schema

Name	Required	Description	Default
`session_id`	Yes
`subject`	Yes
`tools`	Yes
`ttl_seconds`	No
`intent`	Yes
`constraints`	No

TDQS

C2.4/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Lacking annotations, the description only discloses the 'short-lived' nature (relating to ttl_seconds) but omits critical behavioral details: what authorization the lease grants, how the constraints object limits usage, side effects of issuance, or security implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single dense sentence with no filler words; information is front-loaded. However, extreme brevity becomes a liability given the complete absence of schema documentation and annotations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Inadequate for a security-sensitive tool with 6 parameters (including a nested constraints object). Fails to explain the capability model, what the lease authorizes, or the purpose of required fields like 'subject', creating operational risk.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description partially compensates by implying session_id, intent, and ttl_seconds via 'bound to session+intent' and 'short-lived', but leaves 'subject', 'tools', and the nested 'constraints' object completely unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

States the core action (Issue) and resource (capability lease) with binding context (session+intent), but uses domain jargon without explanation and fails to differentiate from sibling 'airlock_audit_tail' or explain what the lease enables.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides no guidance on when to issue capabilities versus using other tools, no security prerequisites, and no warnings about the sensitivity of granting tool access via leases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

http_get_jsonA

Fetch JSON from a public HTTPS API endpoint.

ParametersJSON Schema

Name	Required	Description	Default
`url`	Yes	HTTPS URL to fetch.
`query`	No	Optional query parameters.

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It adds valuable behavioral context by specifying 'public' (implying no auth headers required) and 'JSON' (setting expectation for response parsing), but omits operational details like timeout behavior, redirect handling, or error responses for non-JSON content.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, dense sentence with zero waste. It front-loads the action and precisely qualifies the target resource type and protocol without filler text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 parameters, no output schema), the description adequately covers the essential contract. The 'public' qualifier is crucial for setting correct expectations, though mentioning error handling for non-JSON responses would strengthen completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the schema fully documenting both 'url' and 'query' parameters. The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline expectation for well-documented schemas.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description provides a specific verb ('Fetch'), resource type ('JSON'), and scope ('public HTTPS API endpoint'), clearly positioning this as a generic external HTTP client distinct from domain-specific siblings like weather_hourly and airlock_audit_tail.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

While it lacks explicit 'when-to-use' statements, the description implies usage through the 'public HTTPS API' scope, suggesting external/unauthenticated endpoints versus the internal/domain-specific siblings. However, it does not explicitly direct users to alternatives like weather_hourly for weather data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

weather_hourlyA

Resolve US city/state and fetch hourly weather from Open-Meteo.

ParametersJSON Schema

Name	Required	Description	Default
`city`	Yes
`state`	Yes
`hours`	No

TDQS

A3.7/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full disclosure burden. It successfully indicates the geocoding behavior ('Resolve') and data source ('Open-Meteo'), but omits critical behavioral details like error handling for invalid locations, output format, units (imperial/metric), or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, dense sentence with zero redundancy. Every word contributes essential information (action, scope, data source), making it appropriately sized and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple 3-parameter schema with primitive types and no output schema, the description adequately covers the core function. However, gaps remain: the 'hours' parameter is undocumented, and the absence of annotations or output schema leaves the return structure and units unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, requiring the description to compensate. It implicitly documents the 'city' and 'state' parameters by specifying they are 'US city/state', adding geographic context not present in the raw parameter names. However, it fails to mention the 'hours' parameter or its constraints (1-168, default 24).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ('Resolve', 'fetch') and identifies the exact resource ('hourly weather'). It clearly distinguishes the tool from siblings (airlock_audit_tail, http_get_json) by specifying the weather domain and Open-Meteo data source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies geographic constraints by specifying 'US city/state', hinting at usage boundaries. However, it lacks explicit guidance on when to use versus alternatives (e.g., for non-US locations) or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

4 tool updatesv0.1.0Apr 4, 2026
- First observedairlock_audit_tail
- First observedairlock_issue_capability
- First observedhttp_get_json
- First observedweather_hourly

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

C2.9/5.0

Scored 2026-04-04 05:31 across 4 tools

Disambiguation4/5

Each tool targets a distinct function (provenance auditing, capability issuance, generic HTTP fetching, and weather retrieval) with minimal overlap. An agent can easily distinguish when to use each based on the task requirements.

Naming Consistency3/5

Mixed naming patterns: two tools use 'airlock_' prefix with verbs (issue, audit_tail), while others use 'http_' prefix or no prefix (weather_hourly). The weather tool breaks the verb-first convention used by others, using a noun-adjective pattern instead.

Tool Count3/5

Four tools is acceptably compact but the set suffers from scope confusion, mixing core Airlock security functions with unrelated utility tools (weather, HTTP). This feels like two different servers merged together rather than a cohesive toolset.

Completeness2/5

The Airlock domain (capability management) is severely underdeveloped, offering only issuance and audit tail reading without revocation, validation, or capability listing. The utility tools (weather, HTTP) are also minimal, offering only hourly forecasts and GET requests without parameter customization.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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MCP Airlock

이 프로젝트의 존재 이유

핵심 혁신

컨텍스트 바인딩 권한 임대 (CBCL)

아키텍처

신뢰 경계

주요 기능

2분 퀵스타트

한 줄 명령 로컬 데모 (설치 불필요)

MCP 서버로 실행

CLI

에이전트 통합 예제

설정 템플릿

보안 모델 요약

프로젝트 구조

로드맵

커뮤니티

라이선스

Available Tools

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

evav-gatewayofficial