agent-chaperone
github.com/agent-chaperone/agent-chaperone- Category
- Developer Tools
- Rank
- No. 3478Tools index
Previous survey · No. 3270 ·
- Pricing
- Open Source
- Type
- TOOL
- Use case
- Security & Identity
- Interfaces
- MCP
- GitHub
- 22 stars
- Latest release
- v0.4.1
- Date
About
agent-chaperone is a screening layer that inspects an AI agent's tool calls before they run and their results before the agent reads them, blocking risky, off-task, or secret-leaking actions as well as prompt injections hidden in tool output. It works as an MCP proxy combined with a hooks adapter for a client's built-in tools.
At a glance
agent-chaperone screens tool calls and tool results in supported coding-agent integrations. It is worth starting in shadow mode if you want to see what a policy would flag before you let it hold calls or withhold suspicious output.
Good fit
Developers who control an agent’s MCP configuration or use a supported client hook and want to review tool traffic.
Consider something else when
Skip it if you need process isolation or must keep screened content away from the configured model backend.
Start here
Use a disposable configuration with a mock tool that returns harmless text written like an instruction. In shadow mode, check whether the log flags it and confirms the call was allowed. Compare against a normal response before considering enforcement.
Cost and requirements
Apache-2.0. The documented model screening uses a TypeSafe API key. Without the key, deterministic rules still run. Built-in tool coverage depends on client hooks, while the proxy covers configured MCP servers.
Limits to know
Shadow mode blocks nothing. Model screening sends arguments and results to the backend after pattern-based redaction. The proxy cannot constrain what a tool server does internally, and detection does not guarantee a block.
Related work
Sources checked 2026-11-05. Source-based assessment.
Why it made the leaderboard
Adds a defensive screening layer against prompt injection and risky tool calls for agent harnesses that otherwise execute tool results blindly, addressing a real agent-security gap.
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Editorially curated, with community endorsements as a secondary signal. Corrections welcome.