MCP Airlock

MCP Airlock

Enables secure, zero-trust access to MCP tools through short-lived, signed capability leases that bind tool execution to specific sessions, intents, and constraints. Prevents prompt injection attacks and privilege escalation with dynamic risk scoring, policy enforcement, and tamper-evident audit logging.

Category
Visit Server

README

MCP Airlock

CI License: MIT Python

Zero-trust security gateway for MCP tools.
MCP Airlock turns every tool call into a short-lived, context-bound capability decision with tamper-evident provenance.

Why this exists

Agent tool ecosystems are failing at one painful boundary: the jump from untrusted prompt text to privileged tool execution.

Current patterns are usually one of:

  • static allowlists (agent can call tool X)
  • weak regex filtering
  • post-hoc logs with no integrity guarantees

They fail when prompt injection mutates intent mid-session, causing silent privilege escalation or data exfiltration.

MCP Airlock solves this with a missing primitive for MCP:

  • Capability Leases: short-lived, signed, context-bound rights (session + intent + tool scope + constraints)
  • Context-Aware Policy: dynamic authorization on every call (risk score + tool constraints + lease checks)
  • Tamper-Evident Provenance: append-only hash chain across all allow/deny decisions

Core innovation

Context-Bound Capability Leases (CBCL)

Each tool call is authorized against a signed lease:

  • Bound to session_id
  • Bound to intent_hash
  • Scoped to specific tools
  • Time-limited
  • Optional constraints (e.g. allowed domains, max risk)

If a prompt injection tries to change intent or jump tool scope, execution is denied.

Architecture

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]

Trust boundaries

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

Key features

  • MCP stdio server compatible with initialize, tools/list, tools/call
  • Capability issuance tool: airlock_issue_capability
  • Agent/API usage analytics tool: airlock_usage_stats
  • API exposure measurement tool: airlock_exposure_report
  • Policy enforcement middleware with per-tool risk thresholds
  • Prompt-injection signature scoring
  • SSRF-resistant HTTP tool adapter (http_get_json)
  • Real API integration example (weather_hourly)
  • Tamper-evident provenance log + verification command
  • Sandbox hardening guide for agentic API security
  • CLI for serve/demo/issue/verify/stats/exposure

2-minute quickstart

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

What you will see:

  • a human-friendly summary (handshake, capability, allow/deny, audit integrity)
  • malicious call denied with plain-English reasons
  • signed provenance evidence

One-command local demo (no install)

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

For full JSON payloads during demo:

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

Run as MCP server

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

MCP client setup examples:

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

Example agent integration

Run:

python examples/agent_integration.py

This script:

  • starts Airlock over stdio
  • negotiates MCP initialize/list
  • issues a lease
  • runs a normal tool call
  • runs an injected call that gets blocked

Config template

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"]
    }
  }
}

Security model summary

  1. Agent requests lease via airlock_issue_capability.
  2. Lease is HMAC-signed and includes session, intent_hash, tool_scope, expiry.
  3. Every tools/call request includes _capability and _context.
  4. Airlock enforces:
    • lease validity + signature
    • session and intent continuity
    • risk threshold
    • tool-specific constraints (e.g., domain allowlist)
  5. Decision + evidence is hash-chained to provenance log.

Project structure

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

Roadmap

  • Upstream MCP proxy mode (wrap existing MCP servers transparently)
  • OPA/Rego policy backend
  • OpenTelemetry traces + SIEM sinks
  • Managed capability broker + key rotation
  • Signed replay package for incident response

Community

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured