Install
openclaw skills install @0xwick/telegraphUse 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.
openclaw skills install @0xwick/telegraphTelegraph 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.
| 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
subnetin some tool names is legacy — every provider is a miner today, whether a Bittensor subnet, a hosted model, or a private API.
| 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) |
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.
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: [...]})
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)
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.
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 |
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.
0x036CbD53842c5426634e7929541eC2318f3dCF7eAdd the server to your MCP client config — no clone or build needed; it runs straight from npm:
{
"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.