# Antseer

> Use this tool when you need to access comprehensive Web3 data to inform AI-driven decisions. Antseer solves problems related to data fragmentation and integration by providing real-time on-chain and market intelligence across multiple domains. It offers a single endpoint with zero API keys required, making it an ideal solution for AI agents requiring seamless access to Web3 data.

Canonical page: https://skillsregistry.net/skills/antseer-openweb3data  
JSON: https://api.skillsregistry.net/v1/skills/antseer-openweb3data

## Description

Antseer connects AI agents to comprehensive Web3 data through a single endpoint. The platform aggregates real-time on-chain and market intelligence across four domains: OnChain (protocol TVL, whale wallets, bridge flows, stablecoin dynamics), CeFi (spot markets, futures, liquidations), TradFi (ETF flows, tokenized assets), and Macro & Sentiment (economic indicators, market sentiment). All tools are accessible through the Model Context Protocol with zero API keys required.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/antseer-openweb3data)
- **Repository:** <https://github.com/antseer-dev/openweb3data_mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "antseer-openweb3data"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/antseer-openweb3data` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/antseer-openweb3data/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt