AIronClaw inspects, authenticates and rate-limits every call to your LLMs and MCP servers, stopping prompt injection, tool abuse and data exfiltration before they reach production.
For AI agentsAre you an AI agent? Click here to use AIronClaw →Everything you need to integrate AI models, agents and MCP servers into your application or workflow: securely, observable, and under budget.
Watch a textbook prompt-injection break an unprotected chat, then watch the same attack land harmlessly after a single AIronClaw rule. One AI Judge, one rewrite template, every model behind your stack — no SDK changes.
Guardrails that read prompts the way attackers write them.
Point your SDK at AIronClaw instead of the provider. We intercept, inspect and re-route every call to OpenAI, Anthropic, Bedrock or your own open-source model, with zero app-code changes.
Change one base URL and every request your app makes to a model now flows through AIronClaw. Streaming, function-calling and tool-use all supported, token-by-token.
API-key or JWT authentication in front of every model call, with each key carrying its own model allow-list. Revoke a key in one click — no app-code changes.
Apply your org's input/output policies, redact PII, and cap runaway spend per user or tenant. Centrally, without shipping new app code.
Match a regex against the user message and force the request to a specific model — same API surface, different backend. The proxy re-checks the target against the key's allow-list, so a rule can never smuggle a model the key isn't allowed to call.
AIronClaw sits between your agent and every MCP server it talks to, reading every request and response, stopping injection, RCE, file and secret exfiltration before they reach production.
The firewall parses MCP requests and responses in real time, understanding tool names, arguments and return payloads, not just raw bytes.
Layered detectors flag prompt injection, shell-escape attempts, unexpected network calls, and suspicious argument patterns that try to trick the tool into dangerous behavior.
Every verdict is driven by your policy: allow silently, flag for review, or hard-block. High-signal events become structured audit records the moment they fire.
Append-only audit logs and per-tool attack dashboards make sure your security team sees what the agent tried, when, and why it was stopped.
Mix and match the layers you need. Each module plugs into the same gateway and shares observability, policies and audit logs.
API-key and JWT authentication in front of any MCP server, with per-key allow-lists, budgets and rate limits.
Cap frequency and payload size per tool, per tenant, per agent, with burst and leaky-bucket presets.
Deterministic caching of tool outputs to optimize cost and latency across agents.
Vector-database backed cache answers semantically similar calls without recomputing them.
Persistent, queryable memory so any LLM can pick up where the last session left off on that MCP.
Every input and output captured with token counts and cost, retained for the window you configure.
Every request tagged with input tokens, output tokens and computed cost, ready for the dashboard or for export.
Policy-driven guardrails on tool responses: redaction, classification, compliance checks.
Turn any web page into live, queryable markdown, consumable by any LLM or agent.
Real-time spend per model, key and proxy with daily, weekly and monthly budgets and hard cut-offs.
Append-only audit log, PII redaction on responses and per-key budget enforcement — the building blocks for your own SOC2 / GDPR controls.
Transparent plans for every stage, from your first prototype to enterprise deployments. Free tier is available today; Pro and Enterprise are on the way.
Spin up AIronClaw in front of any MCP server or LLM endpoint in minutes: no SDK changes, no vendor lock-in. Free to start, with the budgets and quotas you set.