Capability Based Access Control For Code Operations

via “granular-permission-based-file-and-command-execution-control”

Autonomous coding agent right in your IDE, capable of creating/editing files, running commands, using the browser, and more with your permission every step of the way.

Unique: Implements operation-level approval gates for every file and command action, preventing unauthorized system modifications—most copilots (Copilot, Codeium) have no explicit approval mechanism; Devin and other agents use sandboxing instead of per-operation approval

vs others: Provides explicit user control over each agent action without relying on sandboxing, making it suitable for untrusted agents, whereas most copilots assume trust and provide no per-operation approval gates

via “role-based access control with granular permission enforcement”

AI platform for building internal business apps.

Unique: Enforces permissions at the server-side query layer before data is serialized, combined with attribute-based rules that evaluate user properties dynamically, ensuring that permission changes take effect immediately without requiring application redeployment

vs others: More granular than Airtable's sharing model because it supports field-level and record-level restrictions, and more flexible than Retool because it includes built-in ABAC evaluation rather than requiring custom middleware

via “command permission system with role-based access control (v0.9+)”

🦞 OpenClaw & Hermes Agent 多引擎 AI 管理面板 — 内置 AI 助手（工具调用 + 图片识别 + 多模态），一键安装 | Tauri v2 跨平台桌面应用 | 11 种语言

Unique: Implements role-based access control at the gateway level with device-level permission enforcement, enabling granular multi-user access without requiring separate authentication infrastructure or external authorization systems.

vs others: Simpler than OAuth/OIDC-based systems but more flexible than simple password protection, providing role-based access control suitable for team deployments without external identity provider dependencies.

via “capability-based access control with @unsafe decorator gating”

AI-powered reverse engineering assistant that bridges IDA Pro with language models through MCP.

Unique: Implements decorator-based capability gating (@unsafe flags) that requires explicit opt-in from MCP clients to access privileged operations (debugging, code execution, memory writes), providing defense-in-depth against accidental or malicious privilege escalation

vs others: More explicit than implicit permission models because @unsafe decorators make privileged operations visible in code, and more flexible than role-based access control because capabilities can be enabled per-client without modifying server code

via “security-first agent sandboxing with capability-based access control”

Local-first personal agentic OS and everything app for coding, knowledge work, web design, automations, and artifacts.

Unique: Implements capability-based security model where agents declare permissions upfront and runtime enforces them through policy engine with prompt injection detection and comprehensive audit logging, rather than relying on implicit trust or post-hoc monitoring

vs others: More granular than basic API key isolation and more practical than full sandboxing (containers/VMs) for local agent deployments, with explicit audit trail vs. implicit logging in most agent frameworks

via “capability-based-access-control-for-code-operations”

I made this for myself, and it seemed like it might be useful to others. I'd love some feedback, both on the threat model and the tool itself. I hope you find it useful!Backstory: I've been using many agents in parallel as I work on a somewhat ambitious financial analysis tool. I was juggl

Unique: Uses kernel-level capability-based access control (seccomp, AppArmor, SELinux) to enforce fine-grained permissions on code execution, preventing even privileged code from performing unauthorized operations — goes beyond traditional role-based access control by operating at the system call level

vs others: More secure than application-level access control because code cannot bypass kernel-level enforcement; more flexible than static allowlists because capabilities can be dynamically configured based on code requirements

via “policy-driven tool access control with dynamic permission evaluation”

** - Enterprise MCP gateway with SSO, RBAC, audit trails, and token vaults for secure, centralized AI agent access control. Deploy via Helm charts on-premise or in your cloud. [webrix.ai](https://webrix.ai)

Unique: Implements a declarative policy engine with attribute-based access control (ABAC) that evaluates complex conditions (time-based, context-aware, rate-limiting) at request time, with in-memory caching to minimize latency while supporting dynamic policy updates

vs others: More expressive than simple RBAC (which only considers roles) and more efficient than evaluating policies in external systems, enabling complex access rules without sacrificing performance

via “skill permission and access control system”

44 plug-and-play skills for OpenClaw — self-modifying AI agent with cron scheduling, security guardrails, persistent memory, knowledge graphs, and MCP health monitoring. Your agent teaches itself new behaviors during conversation.

Unique: Implements fine-grained access control at the skill level with support for both RBAC and ABAC, enabling flexible security policies for multi-tenant agent systems

vs others: More sophisticated than basic role-based access control because it supports context-aware policies and attribute-based decisions, versus static role assignments

via “multi-agent tool access control with role-based enforcement”

Security Proxy for Model Context Protocol — Govern any MCP tool call with ABS Core NRaaS (Non-Repudiation as a Service)

Unique: Implements role-based access control at the MCP gateway layer, allowing fine-grained tool access decisions based on actor identity without requiring changes to individual agent code. Integrates with ABS Core identity management to support centralized role definitions across multiple agents and teams.

vs others: Unlike agent-level tool restrictions (which require per-agent configuration) or LLM-based access control (which is not cryptographically enforceable), gateway-level RBAC provides centralized, auditable, and tamper-proof tool access control.

via “per-tool access control policies”

Security gateway for MCP servers. Shadow-mode logs, per-tool policies, optional Ed25519-signed receipts. npx protect-mcp -- node server.js

Unique: Provides tool-level granularity for access control at the MCP protocol layer rather than requiring each tool to implement its own authorization logic. Centralizes policy enforcement in the gateway rather than distributing it across multiple tool implementations.

vs others: Simpler than implementing authorization in each individual tool, and works with any MCP server without requiring server-side code changes, unlike application-level access control frameworks

via “built-in authentication and authorization enforcement”

** (Python) - Open-source framework for building enterprise-grade MCP servers using just YAML, SQL, and Python, with built-in auth, monitoring, ETL and policy enforcement.

Unique: Integrates declarative policy-as-code (YAML/Python) directly into the MCP request pipeline with support for RBAC and ABAC patterns, evaluated before tool execution, rather than relying on external authorization services or database-level permissions alone

vs others: Provides centralized, MCP-aware access control that can enforce policies across heterogeneous tools and data sources in a single configuration layer, versus scattering authorization logic across individual tool implementations or relying solely on database permissions

via “resource-access-control-with-capability-binding”

AgenShield — AI Agent Security Platform

Unique: Uses capability-based security model where agents receive explicit grants of allowed tools rather than checking permissions at invocation time, enabling efficient enforcement and clear visibility into agent capabilities. Supports context-aware binding where capabilities can vary based on tenant, user, or execution context.

vs others: Implements capability-based security (explicit grants) rather than permission-based (implicit allows), providing stronger isolation guarantees and clearer audit trails

via “configurable access control”

Browse directories and read files within a safe, configurable root. Pull accurate context from local projects and docs without leaving your workflow. Limit access to a chosen root to keep your environment secure.

Unique: Offers a highly customizable access control mechanism through configuration files, unlike static permission models in other tools.

vs others: More flexible than traditional permission systems, allowing for dynamic adjustments based on project needs.

via “context-aware access control for tool execution”

MCP runtime security proxy — intercepts and enforces security policies on MCP tool calls

Unique: Evaluates access control rules against rich execution context (caller identity, environment, time) rather than just tool names, enabling policies that express 'who can call what when'. Uses a declarative rule engine that can combine multiple context attributes in a single policy.

vs others: More expressive than simple allowlist/denylist approaches because it can encode context-dependent policies, whereas basic tool allowlists cannot distinguish between different callers or execution environments.

via “tool exposure with capability-based access control”

MCP server: secure-mcp-server

Unique: Implements capability-based access control at the MCP protocol layer using a declarative capability matrix that applies uniformly to all tools, rather than embedding access checks within individual tool implementations

vs others: Provides centralized, auditable tool access control for MCP servers whereas typical implementations require per-tool authorization logic, reducing code duplication and ensuring consistent security policies

via “access control and permission validation for agent operations”

** - Official MCP Server from [Atlan](https://atlan.com) which enables you to bring the power of metadata to your AI tools

Unique: Enforces Atlan's access control policies at MCP tool invocation level, preventing agents from accessing restricted metadata even if misconfigured; integrates with Atlan's audit system to provide complete traceability of agent operations

vs others: Unlike agents that implement access control logic themselves, Atlan's MCP server enforces policies server-side, ensuring consistent policy application and preventing accidental policy bypass through agent misconfiguration

via “mcp resource and tool access control based on authentication context”

Plug and play auth for Model Context Protocol (MCP) servers

Unique: Implements authorization at the MCP tool/resource level rather than HTTP endpoint level, enabling per-capability access control that aligns with MCP's resource and tool calling model

vs others: More granular than HTTP-level authorization because it can enforce different policies per MCP tool or resource within a single endpoint

via “tool call access control with role-based policies”

Vloex MCP Gateway — stdio proxy for MCP tool call governance

Unique: Implements RBAC at the MCP proxy layer, allowing centralized tool access policies without modifying individual tool implementations or requiring client-side enforcement

vs others: More maintainable than distributing access control logic across multiple MCP servers, and more reliable than client-side enforcement since policies are enforced at the protocol boundary

via “role-based access control (rbac) for agent tool permissions”

Enforceable authorization for MCP tool calls

Unique: Applies RBAC specifically to MCP tool access, enabling role-based governance of agent capabilities at the protocol level rather than requiring application-level role checks in each tool implementation.

vs others: Simpler to understand and implement than attribute-based access control (ABAC) for teams new to authorization; more scalable than per-agent tool whitelists because roles can be reused across many agents.

via “channel-based access control”

MCP server: pubnub-mcp

Unique: Incorporates PubNub's built-in access management features, allowing for fine-grained control over who can access what data in real-time.

vs others: More efficient than building custom access control systems, leveraging PubNub's existing infrastructure.