Telegraph Protocol

SKILL.md

---
name: telegraph
description: Use Telegraph Protocol for verified AI inference. Activate when the user asks for weather forecasts or climate data; deepfake or AI-content detection; LLM completions, image generation, or embeddings via a decentralized network; AI text detection; autonomous signal monitoring across categories like POLITICS, TECHNOLOGY, CLIMATE, HEALTH, ECONOMICS, or GEOPOLITICS; or any task where the user explicitly wants to route inference through the Telegraph network or pay via x402 USDC micropayments. Requires the Telegraph MCP server running with a USDC-funded EVM or Solana wallet.
license: MIT
homepage: https://github.com/telegraphprotocol/telegraph-mcp
metadata:
  version: 1.1.0
  homepage: https://github.com/telegraphprotocol/telegraph-mcp
  documentation: https://docs.telegraphprotocol.com
  keywords: [ai-inference, x402, bittensor, mcp, usdc, deepfake-detection, weather, llm, web3, agent-payments]
  openclaw:
    emoji: "📡"
    requires:
      config: ["mcpServers.telegraph"]
---

# Telegraph Protocol

Telegraph is a permissionless marketplace for verifiable AI inference. Agents pay USDC per request. Miners — which can be Bittensor subnets, OpenAI, open-source models, or any AI API — compete to supply answers. A decentralized validator mesh grades responses using zkTLS-verified ground truth and WASM scoring scripts, reaches BFT consensus, and delivers a cryptographically finalized result.

The native token is **MACHINA**. Every USDC paid for inference flows through an open-market TWAP to buy MACHINA for the miner — demand for intelligence directly drives demand for the token.

---

## MCP Tool Reference

### Free tools (no payment)

| Tool | Purpose |
|------|---------|
| `tg_node_list_subnets` | Full miner catalog — IDs, slugs, endpoints, input/output schemas |
| `tg_node_subnets_health` | Health status of all miner integrations |
| `tg_node_status` | Node identity, public key, chain info |
| `tg_engine_list_subnets` | Engine's view of available miners with capabilities and cost |
| `tg_daemon_categories` | Signal categories in the Daemon database (POLITICS, CLIMATE, TECHNOLOGY, …) |
| `tg_daemon_questions` | Query the Daemon's stored signals — filterable by category, source, time, interest |
| `tg_daemon_health` | Daemon health check |

> The `subnet` in some tool names is legacy — every provider is a **miner** today, whether a Bittensor subnet, a hosted model, or a private API.

### Paid tools (x402 USDC per call)

| Tool | Purpose |
|------|---------|
| `tg_engine_ask` | Auto-routed inference — Engine's LLM router selects the best miner for your query |
| `tg_engine_ask_subnet` | Direct inference to a specific miner by ID |
| Dynamic tools (auto-discovered) | Per-miner tools generated from the live integration registry (see below) |

---

## Access Modes

### 1. Auto-routed inference (recommended)
The Engine classifies your natural language query into an Intent and routes to the highest-ranked miner for that task:

```
tg_engine_ask(query="7-day weather forecast for Dubai")
tg_engine_ask(query="Is this image AI-generated?")
tg_engine_ask(query="Summarize the latest clinical trial results for GLP-1 drugs")
```

The response includes `routing.reasoning` — which subnet was chosen and why.

### 2. Direct miner inference
Route to a specific miner when you know exactly what you want:

```
tg_engine_ask_subnet(subnet_id="18", method="GET", endpoint="/predict", payload={lat: 25.2, lon: 55.3, variable: "hourly"})
tg_engine_ask_subnet(subnet_id="34", method="POST", endpoint="/", payload={image_url: "https://..."})
tg_engine_ask_subnet(subnet_id="102", method="POST", endpoint="/chat", payload={model: "gpt-4o-mini", messages: [...]})
```

### 3. Daemon signal feed (free reads)
The Daemon runs autonomously every 3 hours — collecting data from registered sources (weather APIs, market feeds, news and social feeds), routing questions through miners, and storing verified results. Reading these is free:

```
tg_daemon_categories()
# → live list of categories with current counts

tg_daemon_questions(category="CLIMATE", limit=10)
tg_daemon_questions(category="TECHNOLOGY", sort="interest", min_interest=5)
tg_daemon_questions(source="polymarket", since_hours=24)
```

### 4. Dynamic miner tools (auto-discovered)
On startup, the MCP server fetches the live integration registry and generates per-endpoint tools for every active miner. These update every 5 minutes without restart. The live set changes on-chain — treat the table below as a snapshot, not the source of truth:

| Tool (auto-generated) | Miner | Capability |
|-----------------------|-------|-----------|
| `tg_zeus_predict` | Zeus (18) | Weather forecast |
| `tg_itsai_text_detector_detect` | ItsAI (32) | AI text detection |
| `tg_sapling_ai_detector_detect` | Sapling (33) | AI content detection |
| `tg_bitmind_detect_image` | BitMind (34) | Deepfake image detection |
| `tg_bitmind_detect_video` | BitMind (34) | Deepfake video detection |
| `tg_openai_chat` | OpenAI (102) | LLM chat |
| `tg_openai_images_generate` | OpenAI (102) | Image generation |
| `tg_openai_embed` | OpenAI (102) | Text embeddings |
| `tg_openai_moderate` | OpenAI (102) | Content moderation |

Use `tg_node_list_subnets` to see the current live catalog with full schemas.

---

## Active Intents

The Engine's LLM router maps queries to canonical Intents:

| Category | Intents |
|----------|---------|
| Language | `LANGUAGE_GENERATION`, `CHAT_COMPLETION`, `TEXT_GENERATION`, `HIGH_PERFORMANCE_INFERENCE`, `EMBEDDINGS`, `CONTENT_MODERATION` |
| Weather | `WEATHER_CHECK`, `WEATHER_FORECAST`, `STORM_ALERT`, `WEATHER_RISK_ASSESSMENT` |
| Vision | `MULTIMODAL_INFERENCE`, `IMAGE_GENERATION`, `TEXT_TO_IMAGE` |
| Search | `WEB_SEARCH`, `TWITTER_SEARCH`, `NEWS_SEARCH`, `RESEARCH_SYNTHESIS`, `FACT_CHECK` |
| Authenticity | `DEEPFAKE_DETECTION`, `MEDIA_AUTHENTICITY_CHECK`, `AI_TEXT_DETECTION`, `TEXT_AUTHENTICITY_CHECK`, `IMAGE_VERIFICATION`, `VIDEO_VERIFICATION` |
| Tasks | `TASK_COMPLETION`, `AGENT_TASK` |

---

## Payments

All paid calls use **x402** — an HTTP-native micropayment protocol. The MCP server handles the full flow transparently: receives the 402 challenge, signs the USDC transfer using your configured private key, and retries. The agent never sees the payment step.

- **Network**: Base Sepolia (testnet) — USDC `0x036CbD53842c5426634e7929541eC2318f3dCF7e`
- **Typical cost**: $0.01 – $0.05 per inference call
- **Pricing**: miner's floor price × demand multiplier (rises with 24h request volume for the Intent)
- **Use a burner wallet** — fund with only the USDC you need; never use a main wallet
- **Key custody**: the private key lives only in the local MCP server's process environment. It is never sent to the model, never appears in tool inputs or outputs, and never leaves the machine — only signed x402 payment authorizations do.

---

## Setup

Add the server to your MCP client config — no clone or build needed; it runs straight from npm:

```json
{
  "mcpServers": {
    "telegraph": {
      "command": "npx",
      "args": ["-y", "telegraph-protocol-mcp"],
      "env": {
        "TELEGRAPH_NODE_URL": "http://13.237.89.59:7044",
        "TELEGRAPH_ENGINE_URL": "http://13.237.89.59:8080",
        "TELEGRAPH_DAEMON_URL": "http://13.237.89.59:8081",
        "TELEGRAPH_EVM_PRIVATE_KEY": "0xyour_burner_wallet_key"
      }
    }
  }
}
```

Config file locations: Claude Desktop `claude_desktop_config.json` · Cursor MCP settings · OpenClaw `~/.openclaw/openclaw.json`. On OpenClaw this skill gates on the `mcpServers.telegraph` config entry — it stays dormant (zero prompt overhead) until the server above is configured.

Full integration guides for Claude Desktop, Cursor, ElizaOS, LangChain, Goose, and others are in the [README](https://github.com/telegraphprotocol/telegraph-mcp#readme).