AgentAudit MCP
Provides an immutable, tamper-evident audit trail for AI agents, enabling event logging with cryptographic chaining, search, verification, and statistics.
README
<p align="center"> <img src="assets/logo.png" width="80" alt="AgentPay"> </p>
AgentAudit MCP
Your agent now has an immutable, tamper-evident log of every action it takes — each event cryptographically linked to the previous one so any modification breaks the chain and is immediately detectable.
What your agent can do
- Log any of 16 event types (payments, tasks, disputes, identity checks, messages) with a SHA-256 hash that includes the previous event's hash
- Retrieve the full history of any agent by ID — every action, in order, with timestamps
- Search across the audit trail by agent, event type, severity level, or date range
- Verify chain integrity between any two events and get a per-event pass/fail breakdown showing exactly which link was tampered
- Track five severity levels —
info,notice,warning,error,critical— for compliance triage - Get statistics across the entire audit trail: events by type, by severity, and most active agents
Installation
Requires: Python 3.10+, mcp and fastmcp packages.
pip install mcp fastmcp
Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"agent-audit": {
"command": "python",
"args": ["/absolute/path/to/agent-audit-mcp/server.py"]
}
}
}
Cursor — add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"agent-audit": {
"command": "python",
"args": ["/absolute/path/to/agent-audit-mcp/server.py"]
}
}
}
Data is stored locally at ~/.agentaudit/chain.json. No data leaves your machine.
Tool Reference
| Tool | Description | Key params |
|---|---|---|
audit_log |
Log an event and append it to the hash chain | event_type (one of 16), agent_id, severity, details_json |
audit_get_event |
Retrieve full event details by ID | event_id |
audit_search |
Filter events by agent, type, severity, or date range | agent_id, event_type, severity, from_date, to_date, max_results |
audit_get_agent_history |
All events for one agent, newest first | agent_id, max_events |
audit_verify_chain |
Check SHA-256 chain integrity between two events; returns per-event PASS/FAIL | from_event_id, to_event_id |
audit_stats |
Summary: total events, breakdown by type/severity, top 5 active agents | — |
Supported event types: task_created, task_assigned, task_completed, task_failed, payment_sent, payment_received, payment_refunded, dispute_raised, dispute_resolved, identity_verified, capability_used, agent_registered, agent_rated, agent_offline, message_sent, message_received
Security
Audit data is written atomically (write-to-temp, then os.replace) to prevent partial writes from corrupting the chain. The hash covers every field including the previous event's hash — you cannot insert, delete, or modify any event without breaking all subsequent hashes. audit_verify_chain recomputes each hash from scratch rather than trusting stored values.
All data is stored locally. No network requests are made by this server.
Pricing
| Plan | Price | Included |
|---|---|---|
| Pro | $19/month | Unlimited audit events, full chain verification |
License
Proprietary — see subscription terms. Source: github.com/Rumblingb/agent-audit-mcp
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.