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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

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

Summary

agent-trust-stack-mcp MCP server](https://glama.ai/mcp/servers/alexfleetcommander/agent-trust-stack-mcp/badges/score.svg)](https://glama.ai/mcp/servers/alexfleetcommander/agent-trust-stack-mcp) 🐍 πŸ“‡ ☁️ 🏠 🍎 πŸͺŸ 🐧 - Cryptographic provenance, bilateral...

README.md

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 β€” 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 β€” 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 | | verify_agent_identity | Verify an agent's identity via Agent Card URL | | get_trust_evidence | Get combined trust evidence (CoC + ARP) for an agent |

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): ``bash 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

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

Log activity

β†’ 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

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

Rate another agent

β†’ 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

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

Running Directly

# stdio mode (default β€” 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.

Local Package vs Hosted API

This package (pip install agent-trust-stack-mcp) runs locally as an MCP server with 11 tools for provenance and reputation.

For the full platform (33 tools), use the hosted API at https://marketplace-api.vibeagentmaking.com:

| Feature | Local Package | Hosted API | |---------|--------------|------------| | CoC provenance | Yes (11 tools) | Yes | | ARP reputation | Yes | Yes | | Agent marketplace | No | Yes | | AgentSpace (agent LinkedIn) | No | Yes | | Hosted CoC chains ($29/mo) | No | Yes | | Trust Handshake (ATHP) | No | Yes | | Total tools | 11 | 41 |

The hosted API is also MCP-compatible β€” connect to it the same way, just point at the remote URL. See vibeagentmaking.com/llms.txt for full API documentation.

Registry Listings

Part of the Agent Trust Stack

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

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

Full stack: pip install agent-trust-stack

Security

VAM-SEC v1.0 β€” 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 β€” Copyright (c) 2026 AB Support LLC

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