agent-trust-stack-mcp 0.1.0

MCP server exposing Agent Trust Stack tools — Chain of Consciousness provenance logging and Agent Rating Protocol reputation scoring for autonomous AI agents

Agent Trust Stack MCP Server

MCP (Model Context Protocol) server exposing the Agent Trust Stack tools so any MCP-compatible AI agent can use them natively.

Provides Chain of Consciousness (CoC) provenance logging and Agent Rating Protocol (ARP) reputation scoring — the two operational protocols from the 7-protocol Agent Trust Stack.

Tools

Tool	Description
coc_init	Initialize a new cryptographic hash chain (genesis block)
coc_add	Append an entry — learn, decide, create, error, note, milestone, session_start/end
coc_verify	Verify chain integrity (hash linkage, sequence, completeness)
coc_status	Get chain stats (length, agents, time span, event types)
coc_tail	Get the last N entries
coc_anchor	Submit chain hash for external timestamping (OTS + RFC 3161 TSA)
arp_rate	Submit a bilateral blind rating for another agent
arp_check	Check an agent's reputation score
trust_stack_info	Get info about all 7 protocols with whitepaper links

Resources

URI	Description
trust-stack://protocols	Overview of all 7 protocols with links
trust-stack://installation	Installation instructions

Installation

pip install agent-trust-stack-mcp

For proper OpenTimestamps .ots file format (optional):

pip install agent-trust-stack-mcp[ots]

Configuration

Add to your MCP client config (Claude Code, Cursor, etc.):

{
  "mcpServers": {
    "agent-trust-stack": {
      "command": "agent-trust-stack-mcp",
      "args": []
    }
  }
}

Environment Variables

Variable	Default	Description
COC_CHAIN_DIR	./chain	Directory for chain files
ARP_RATINGS_DIR	./ratings	Directory for rating files

Custom data directories

{
  "mcpServers": {
    "agent-trust-stack": {
      "command": "agent-trust-stack-mcp",
      "args": [],
      "env": {
        "COC_CHAIN_DIR": "/path/to/my/chain",
        "ARP_RATINGS_DIR": "/path/to/my/ratings"
      }
    }
  }
}

Usage Examples

Once connected, any MCP-compatible agent can call these tools directly:

Start a provenance chain

→ coc_init(agent="my-agent")
← { "status": "chain_initialized", "sequence": 0, "entry_hash": "a1b2c3..." }

Log activity

→ coc_add(event_type="learn", data="Processed 500 documents from dataset X", agent="my-agent")
← { "status": "entry_added", "sequence": 1, "entry_hash": "d4e5f6..." }

Verify chain integrity

→ coc_verify()
← { "is_valid": true, "entry_count": 42, "agents": {"my-agent": 42} }

Rate another agent

→ arp_rate(rater="agent-a", ratee="agent-b", score=0.8, context="Delivered accurate research")
← { "status": "rating_recorded", "rater_hash": "7f8a9b...", "score": 0.8 }

Check reputation

→ arp_check(agent_id="agent-b")
← { "rating_count": 5, "average_score": 0.72, "unique_raters": 3 }

Running Directly

# stdio mode (default — for MCP client connections)
agent-trust-stack-mcp

# Or via Python module
python -m agent_trust_stack_mcp

How It Works

Chain of Consciousness (CoC): An append-only JSONL file where each entry contains a SHA-256 hash linking it to the previous entry, creating a tamper-evident log. Any modification to earlier entries breaks the hash chain, making tampering detectable. Optional external anchoring via OpenTimestamps (Bitcoin) and RFC 3161 TSA provides independent timestamp proof.

Agent Rating Protocol (ARP): Agents rate each other on a -1.0 to 1.0 scale after interactions. Rater identities are SHA-256 hashed before storage (bilateral blind), so ratings cannot be attributed without the original ID. Reputation is the aggregate of all received ratings.

Registry Listings

• Smithery — agent-trust-stack
• Glama — agent-trust-stack
• mcp.so — agent-trust-stack
• MCP Servers — agent-trust-stack

Part of the Agent Trust Stack

This MCP server exposes tools from the Agent Trust Stack — seven interlocking protocols for autonomous AI agent trust infrastructure:

1. Chain of Consciousness — Provenance logging (this server)
2. Agent Rating Protocol — Reputation scoring (this server)
3. Agent Service Agreements — Machine-readable contracts
4. Agent Justice Protocol — Dispute resolution
5. Agent Lifecycle Protocol — Birth, migration, retirement
6. Agent Matchmaking — Capability discovery
7. Context Window Economics — Token resource management

Full stack: pip install agent-trust-stack

Security

VAM-SEC v1.0 — All CoC and ARP operations are local file I/O. No credentials are required or stored. No network calls are made except during optional coc_anchor (OTS calendar servers + freeTSA.org). No API keys needed.

License

Apache-2.0 — Copyright (c) 2026 AB Support LLC