Enterprise MCP Gateway

    1

    Securely bridge AI agents to internal REST APIs with RBAC, PII masking, and audit logging via MCP.

    Free

    Security scanned

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+22 more

    Enterprise MCP Gateway

    Example session with this skill installed

    Help me connect my Claude Desktop agent to our internal inventory API using the enterprise gateway. The API spec is at /opt/specs/inventory.yaml and my token is 'dev-token-99'.

    • Read your context and instructions
    • Compiled the enterprise mcp gateway

    I have generated the configuration files required to bridge your internal inventory API to Claude Desktop via the Enterprise MCP Gateway. This setup ensures all calls are logged and PII is redacted before reaching the agent.

    Gateway Configuration and Connection

    First, create your config.yaml to define the connector and security rules:

    
# config.yaml
connectors:
  - name: inventory-api
    spec_file: "/opt/specs/inventory.yaml"
    base_url: "http://internal-inventory.local:8081"

governance:
  mask_secrets: true
  tokens:
    dev-token-99:
      role: developer
  roles:
    developer:
      allowed_tools:
        - "inventory-api:list_*"
        - "inventory-api:get_*"

sanitizer:
  sensitive_keys:
    - "api_key"
    - "session_id"
    - "credit_card"

audit:
  log_path: "logs/mcp-audit.json"
  format: "json"

    Next, update your claude_desktop_config.json to include the gateway:

    {
  "mcpServers": {
    "enterprise-gateway": {
      "command": "/usr/local/bin/mcp-gateway",
      "args": [
        "--config", "/absolute/path/to/config.yaml",
        "--token", "dev-token-99"
      ]
    }
  }
}

    Next steps

    1. Ensure the mcp-gateway binary has execution permissions (chmod +x).
    2. Verify the base_url is reachable from your local machine.
    3. Restart Claude Desktop to initialize the MCP tools.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Exposing internal enterprise APIs to AI agents often creates security and compliance gaps. This skill provides a secure Model Context Protocol (MCP) gateway that bridges AI coding agents to internal REST and OpenAPI services with enterprise-grade controls. It ensures that internal tools are only accessible via governed channels, preventing unauthorized access and data leakage.

    What it does

    • OpenAPI bridging connects agents like Claude, Cursor, and Gemini to internal REST services by converting OpenAPI 3.0 specs into MCP tools.
    • RBAC enforcement applies granular tool-level permissions per agent or team using token-based role mapping.
    • Data redaction masks sensitive info including credit cards, SSNs, and secrets using zero-allocation in-flight PII filtering.
    • Audit logging generates immutable JSON logs of every tool execution for SIEM compliance and security forensics.
    • Flexible transport supports local execution via stdio for IDE agents or centralized deployment via SSE for shared team servers.

    How it works

    1. Define connectors in a config.yaml file pointing to absolute paths of OpenAPI 3.0 specification files.
    2. Configure governance by mapping tokens to roles and defining allowed tool globs and PII masking patterns.
    3. Launch the binary using the --config flag and selecting the transport mode (stdio or sse).
    4. Connect the agent by adding the gateway command and token to the agent's MCP configuration file.

    Frameworks & tools

    The gateway is built as a Go binary and supports OpenAPI 3.0 specifications. It integrates with Claude Code, Claude Desktop, Cursor, Antigravity, and Gemini CLI.

    Why this beats prompting it yourself

    Prompting an agent to call an API manually lacks security controls and auditability. This skill moves governance to the infrastructure layer, ensuring PII is redacted and access is logged before the LLM ever sees the data.

    Use cases

    • Providing developers with AI-driven access to internal CRM or ERP APIs while masking customer PII.
    • Restricting a support agent to read-only tool access while allowing an admin agent full write capabilities.
    • Maintaining a centralized audit trail of all actions performed by AI agents against internal production environments.

    Known limitations

    The gateway currently only supports OpenAPI 3.0 REST specifications. GraphQL and gRPC backends are not supported. Config files must use absolute paths to resolve OpenAPI specs correctly.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Gateway MCP

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