@helm-protocol/ttt-mcp

Reference implementation of draft-helmprotocol-tttps-00 (IETF Experimental)

MCP Server for OpenTTT — Proof of Time tools for AI agents

The Problem: Workflow Amnesia

Large Claude Code workflows — 20-agent Dynamic Workflows, multi-day multi-session projects, 100K+ token contexts — all face the same failure mode: context compression erases action history.

Agent B has no memory of what Agent A decided. Agent A resumes after compression with no record of its own prior steps. Duplicate work. Lost decisions. State corruption.

ttt-mcp is the external nervous system that survives context compression.

Every workflow step is anchored to a cryptographic timestamp on an external server — physically separate from Claude's context window. When compression happens, agents query their exact action history through the MCP tools and resume with full causal context.

Claude workflow → [context compressed] → agents call pot_query(eventId)
                                         → external server returns full timeline
                                         → workflow resumes, zero lost state

Mathematical Guarantee

Quick Start

# Claude Desktop
```json
{
  "mcpServers": {
    "ttt": {
      "command": "npx",
      "args": ["-y", "@helm-protocol/ttt-mcp"]
    }
  }
}

Add TTT_API_KEY for unlimited calls (free tier: 100 calls/day per IP).

Tools

Tool Parameters

pot_generate

Stamp a workflow step with a cryptographic timestamp. For Claude Code: use eventId + prevEventId. For DeFi: use txHash + chainId + poolAddress. One of eventId or txHash is required.

pot_query

Query Proof of Time records. Use eventId for O(1) exact lookup after context compression.

pot_graph

Traverse the causal chain from any step. Returns backward chain (ancestors) and forward chain (descendants).

pot_verify

pot_stats

pot_health

No parameters.

pot_checkpoint

Creates a compressed rollup checkpoint of workflow history.

Use when: Approaching context limit, before long tasks, or every ~100 events.

Returns:

• checkpointId — unique checkpoint identifier

• rollupSummary — compressed event history (depth-adaptive: full/compact/minimal/rollup)

• chainIntact — whether the causal chain is unbroken

• nextCheckpointHint — recommended events before next checkpoint

Depth-adaptive compression:

Use Cases

1. Claude Code Workflow — Amnesia Prevention

Problem: A 20-agent Dynamic Workflow refactors a 500K-line codebase over hours. After each context compression, agents have no memory of what they already processed. Duplicate work. State corruption.

Solution: Each agent stamps its steps with pot_generate(eventId, prevEventId). After compression, it calls pot_query(eventId) to recover its exact action history — what ran, when, in what order — from the external server. The server is outside Claude's context window; compression never touches it.

// Agent starts a workflow step
const pot = await client.callTool({
  name: "pot_generate",
  arguments: {
    eventId: "refactor_auth_module_step3",
    prevEventId: "refactor_auth_module_step2"
  }
});
// pot.potHash — cryptographic proof this step happened at this time

// After context compression, agent recovers its history:
const history = await client.callTool({
  name: "pot_query",
  arguments: { eventId: "refactor_auth_module_step3" }
});
// history.local[0] — exact record: timestamp, prevEventId, potHash
// history.found: true — O(1) lookup, collision probability 2⁻²⁵⁶

// Traverse full causal chain:
const chain = await client.callTool({
  name: "pot_graph",
  arguments: { eventId: "refactor_auth_module_step3", depth: 20 }
});
// chain.backwardChain — all ancestor steps in chronological order
// chain.forwardChain — steps that follow this one

Before a long task or every ~100 events — create a checkpoint:

// Compress workflow history before context fills up — by causal range:
const checkpoint = await client.callTool({
  name: "pot_checkpoint",
  arguments: {
    fromEventId: "refactor_auth_module_step1",
    toEventId: "refactor_auth_module_step3"
  }
});
// checkpoint.checkpointId — store this; resume from it after compression
// checkpoint.rollupSummary — depth-adaptive compressed history (10–200 tokens/event)
// checkpoint.chainIntact: true — causal chain verified unbroken
// checkpoint.nextCheckpointHint: 87 — suggested events before next checkpoint

// Or compress by time window with a token budget:
const checkpoint = await client.callTool({
  name: "pot_checkpoint",
  arguments: {
    startTime: Date.now() - 3_600_000,  // last 1 hour
    maxTokens: 1500
  }
});

// After context compression, restore from checkpoint instead of re-querying all events:
const history = await client.callTool({
  name: "pot_query",
  arguments: { eventId: checkpoint.checkpointId }
});
// Full causal context restored in a single call

Outcome: Zero duplicate work. Full workflow timeline recoverable even after complete context resets.

2. MEV Bot — Transaction Ordering Proof

Problem: You got front-run. You can't prove it — mempool timestamps are per-node, unsigned, non-authoritative.

Solution: Call pot_generate before every submission. The PoT receipt is cryptographically signed by three independent time sources (NIST, Google, Cloudflare), anchored on Base Sepolia TTT ERC-1155. If front-running occurs, you have a timestamped, on-chain record predating the attacker's block inclusion.

const pot = await client.callTool({
  name: "pot_generate",
  arguments: { txHash: pendingTxHash, chainId: 8453, poolAddress: "0x..." }
});
// pot.potHash — your evidence, timestamped by NIST+Google+Cloudflare

3. DEX Protocol — Sandwich Deterrence

Solution: Integrate TTTHookSimple (Uniswap V4 hook, Base Sepolia: 0x8C633b05b833a476925F7d9818da6E215760F2c7). Honest builders get turbo mode. Tampered sequences get full mode (exponential backoff). Economics, not governance.

4. Hedge Fund / Prop Desk — MiFIR Art.22c Compliance

Problem: MiFIR Article 22c / RTS 25 requires microsecond-precision UTC-synchronized timestamps. Hardware PTP appliances cost $50K–$500K.

Solution: pot_generate produces an Ed25519-signed timestamp with uncertainty bound and multi-source attestation. Structurally compatible with RTS 25 audit record requirements. One API call per trade.

const audit = await client.callTool({
  name: "pot_generate",
  arguments: { txHash: tradeHash, chainId: 8453 }
});
// audit.timestamp: nanosecond precision
// audit.uncertainty: ±ms bound (RTS 25 required field)
// audit.confidence: fraction of sources that agreed

Outcome: MiFIR-grade audit trail. IETF standardized via draft-helmprotocol-tttps-00.

5. Multi-Agent Coordination — Causal Order Proof

Problem: When multiple AI agents interact in a pipeline, the causal order matters for debugging and audit. Agent logs are unverifiable.

Solution: Each agent stamps its action with pot_generate. The potHash chain is independently verifiable. pot_graph reconstructs who did what and in what order.

Rate Limits & Pricing

Free Tier:   100 calls/day per IP — no API key needed
BOT Tier:    $199/mo — unlimited, SLA
DEX Tier:    $499/mo — unlimited, priority support
FUND Tier:   $2K+/mo — enterprise, dedicated infra

Contact: heime.jorgen@proton.me

Requirements

• Node.js >= 18

• Network access for time synthesis (HTTPS to time.nist.gov, time.google.com, time.cloudflare.com)

Learn More

• OpenTTT SDK — The underlying SDK

• IETF Draft: draft-helmprotocol-tttps-00 — TTTPS Protocol Specification

• Helm Protocol — GitHub

License

BSL-1.1 — free for non-commercial use.

Commercial use (production bots, hedge funds, prop desks) requires a license.

Change Date: 2029-05-28 → Apache 2.0