agentseal-mcp

JoeyBrar/agentseal-mcp
1 starsMITCommunity

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

JoeyBrar/agentseal-mcp MCP server](https://glama.ai/mcp/servers/JoeyBrar/agentseal-mcp/badges/score.svg)](https://glama.ai/mcp/servers/JoeyBrar/agentseal-mcp) 📇 🏠 - Action logs for AI agents.

README.md

agentseal-mcp

![agentseal-mcp MCP server](https://glama.ai/mcp/servers/JoeyBrar/agentseal-mcp)

MCP server for AgentSeal. Tamper-proof audit logs for AI agents, using SHA-256 hash chains.

Every agent action is recorded in a hash chain. With this, you can actually prove to your clients that your agent did what it said it did.

Setup

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "agentseal": {
      "command": "npx",
      "args": ["-y", "agentseal-mcp"],
      "env": {
        "AGENTSEAL_API_KEY": "as_sk_your_key_here"
      }
    }
  }
}

Restart Claude Desktop after saving.

Cursor / Other MCP hosts

Same configuration — add the server with your API key.

Environment variables

| Variable | Required | Description | |---|---|---| | AGENTSEAL_API_KEY | Yes | Your API key from agentseal.io | | AGENTSEAL_URL | No | Custom API base URL (defaults to production) |

Tools

record_action

Record an agent action to the audit trail. Call this after significant actions to create a cryptographically chained record of what happened and why.

| Parameter | Type | Required | Description | |---|---|---|---| | agent_id | string | Yes | Identifier for the agent (e.g. research-bot) | | action_type | string | Yes | What kind of action (e.g. email:send, file:write, api:call) | | action_params | object | No | Details of the action | | reasoning | string | No | Why the agent decided to take this action | | authorized_by | string | No | Who or what approved the action |

Returns a sequence number and SHA-256 hash confirming the entry was chained.

query_actions

Look up previously recorded actions from the audit trail. Use this to check what actions have been taken or recall past decisions.

| Parameter | Type | Required | Description | |---|---|---|---| | agent_id | string | No | Filter by agent | | action_type | string | No | Filter by action type | | limit | number | No | Max entries to return (default 20) |

verify_chain

Verify the integrity of the hash chain. Each entry's SHA-256 hash includes the previous entry's hash — if any record was modified, the chain breaks and this reports where.

| Parameter | Type | Required | Description | |---|---|---|---| | agent_id | string | No | Verify chain for a specific agent. If omitted, verifies all entries. |

Returns the number of entries verified and whether the chain is intact.

How it works

Each recorded action is hashed with SHA-256. That hash includes the previous entry's hash, forming a chain. Modify any record and every hash after it changes — verify_chain catches it instantly.

Get an API key

Sign up at agentseal.io. Free to use.

Python SDK

For direct integration without MCP: pip install agentseal-sdk. See agentseal-sdk.

License

MIT

Related MCP servers

Browse all →