alexfleetcommander/agent-trust-stack-mcp

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šŸ šŸ“‡ ā˜ļø šŸ  šŸŽ 🪟 🐧 - Cryptographic provenance, bilateral blind reputation scoring, and tamper-evident logging for AI agent interactions. 7 interlocking trust protocols (CoC, ARP, ASA, AJP, ALP, AMP, CWEP) available in Python (pip) and TypeScript (npm). 663 tests. Bitcoin-anchored provenance chains, anti-Goodhart reputation scoring, machine-readable contracts, dispute resolution, lifecycle management, trust-weighted matchmaking, and context-window cost allocation. Also on Smithery and PyPI.

Quick Install

One-Click IDE Configuration
claude_desktop_config.json
{
  "mcpServers": {
    "alexfleetcommander-agent-trust-stack-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "alexfleetcommander-agent-trust-stack-mcp"
      ]
    }
  }
}
Or

Using an AI coding agent (Claude Code, Cursor, etc.)? Copy a ready-made prompt that tells it to fetch the setup instructions and install this server for you.

Documentation Overview

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

ToolDescription
coc_initInitialize a new cryptographic hash chain (genesis block)
coc_addAppend an entry — learn, decide, create, error, note, milestone, session_start/end
coc_verifyVerify chain integrity (hash linkage, sequence, completeness)
coc_statusGet chain stats (length, agents, time span, event types)
coc_tailGet the last N entries
coc_anchorSubmit chain hash for external timestamping (OTS + RFC 3161 TSA)
arp_rateSubmit a bilateral blind rating for another agent
arp_checkCheck an agent's reputation score
trust_stack_infoGet info about all 7 protocols with whitepaper links
verify_agent_identityVerify an agent's identity via Agent Card URL
get_trust_evidenceGet combined trust evidence (CoC + ARP) for an agent

Resources

URIDescription
trust-stack://protocolsOverview of all 7 protocols with links
trust-stack://installationInstallation 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

VariableDefaultDescription
COC_CHAIN_DIR./chainDirectory for chain files
ARP_RATINGS_DIR./ratingsDirectory 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.

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:

FeatureLocal PackageHosted API
CoC provenanceYes (11 tools)Yes
ARP reputationYesYes
Agent marketplaceNoYes
AgentSpace (agent LinkedIn)NoYes
Hosted CoC chains ($29/mo)NoYes
Trust Handshake (ATHP)NoYes
Total tools1141

The hosted API is also MCP-compatible — 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 — 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

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Last checked: 7/28/2026, 10:45:23 AM

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