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Constitutional guardrails and loop detection for AI agents
Constitutional guardrails and loop detection for AI agents
Agent-guard-mcp is a well-structured MCP server for detecting infinite agent loops with appropriate authentication, input validation, and permissioning. The codebase uses standard MCP SDK patterns and Zod validation. No critical vulnerabilities or malicious patterns detected. Minor code quality findings do not significantly impact security posture. Supply chain analysis found 4 known vulnerabilities in dependencies (0 critical, 3 high severity). Package verification found 1 issue.
4 files analyzed · 9 issues found
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Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-mdfifty50-boop-agent-guard": {
"args": [
"-y",
"agent-guard-mcp"
],
"command": "npx"
}
}
}From the project's GitHub README.
MCP server that detects and prevents infinite agent loops — the #1 reliability problem in agentic systems.
Provides circuit breakers, pattern detection, stuck-agent analysis, and recovery recommendations via the Model Context Protocol.
npx agent-guard-mcp
Add to claude_desktop_config.json:
{
"mcpServers": {
"agent-guard": {
"command": "npx",
"args": ["agent-guard-mcp"]
}
}
}
git clone https://github.com/mdfifty50-boop/agent-guard-mcp.git
cd agent-guard-mcp
npm install
node src/index.js
Register an agent for monitoring.
| Param | Type | Default | Description |
|---|---|---|---|
agent_id | string | required | Unique agent identifier |
max_iterations | number | 100 | Max iterations before forced stop |
progress_threshold | number | 0.3 | Min unique/total action ratio to be "making progress" |
Log an agent action for loop detection. Maintains a rolling window of the last 50 actions.
| Param | Type | Default | Description |
|---|---|---|---|
agent_id | string | required | Agent identifier |
tool_name | string | required | Tool being called |
args | object | required | Arguments passed |
result_preview | string | "" | Brief result preview (max 200 chars) |
Returns early warnings when repeated patterns are detected.
Check if an agent is stuck in an infinite loop.
| Param | Type | Description |
|---|---|---|
agent_id | string | Agent to check |
Returns:
is_stuck — booleanconfidence — 0.0 to 1.0pattern — healthy, exact_repeat, low_diversity, or exact_repeat_and_low_diversitysuggestion — human-readable recovery advicerepeated_actions — list of repeated signatures with countsConfigure automatic intervention when action patterns repeat.
| Param | Type | Default | Description |
|---|---|---|---|
agent_id | string | required | Agent identifier |
max_repeats | number | 3 | Trigger after N identical actions |
action | string | "warn" | "warn", "block", or "suggest_alternative" |
Pre-flight check before executing a tool. Call this BEFORE the actual tool call.
| Param | Type | Description |
|---|---|---|
agent_id | string | Agent identifier |
proposed_tool | string | Tool about to be called |
proposed_args | object | Arguments about to be passed |
Returns proceed: false when the circuit breaker fires (block mode only).
Detailed analysis of why an agent is stuck.
| Param | Type | Description |
|---|---|---|
agent_id | string | Agent to analyze |
Returns: action history, pattern analysis, token waste estimate, diversity ratio, top repeated patterns, and recovery recommendations.
Overview of all monitored agents. No parameters.
Returns all agents sorted by risk score with their status (STUCK/HEALTHY), action counts, and circuit breaker config.
| URI | Description |
|---|---|
agent-guard://agents | All monitored agents with current status |
1. register_agent — at agent startup
2. Before each tool call:
a. check_circuit_breaker — should this action proceed?
b. Execute the tool
c. log_action — record what happened
3. Periodically:
- detect_loop — am I stuck?
- get_health_dashboard — how are all agents doing?
4. On stuck detection:
- get_stuck_report — what went wrong and how to recover
npm test
MIT
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