About Scry
Scry is an MCP server that wraps public Scry corpus endpoints as tools for agents, including free IPv4 lookups. It uses a stateless proxy with Streamable HTTP transport.
Key features
- 01Free IPv4 lookups
- 02Wrap public Scry API endpoints
- 03Use Streamable HTTP transport
Use cases
- 01Check whether an IPv4 address appears in the corpus
- 02Query an IP address from an agent workflow
MCP support
The MCP server exposes Scry's IPv4 lookup endpoint through the `scry_check` tool, using Streamable HTTP transport.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://mcp.tunnelmind.ai/mcpclaude mcp add --transport http ai-tunnelmind-scry https://mcp.tunnelmind.ai/mcp{"mcpServers":{"ai-tunnelmind-scry":{"type":"http","url":"https://mcp.tunnelmind.ai/mcp"}}}Open in Cursor{"servers":{"ai-tunnelmind-scry":{"type":"http","url":"https://mcp.tunnelmind.ai/mcp"}}}Open in VS Code{"mcpServers":{"ai-tunnelmind-scry":{"type":"http","url":"https://mcp.tunnelmind.ai/mcp"}}}{"mcpServers":{"ai-tunnelmind-scry":{"serverUrl":"https://mcp.tunnelmind.ai/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
12This tool takes no parameters.
Details
From the project READMEscry-mcp
MCP (Model Context Protocol) server for the Scry corpus. Wraps the scry-api public endpoints as agent-callable tools.
Hosted at mcp.tunnelmind.ai. MCP spec version 2025-03-26. Streamable HTTP transport.
Tools (v0.1)
| Tool | Wraps | Tier |
|---|---|---|
scry_check | GET /v1/check/{ip} | Free |
Future tools (deferred to defender tier; need ATAP attestation):
scry_watch— subscribe to state changes for an IP/domainscry_actor— full actor profilescry_campaign— campaign detail
Wire protocol
POST https://mcp.tunnelmind.ai/mcp
Content-Type: application/json
{"jsonrpc":"2.0","id":1,"method":"initialize"}
Methods:
initialize— handshake, returns{ protocolVersion, capabilities, serverInfo }notifications/initialized— client → server notification (returns 204)tools/list— returns{ tools: [...] }tools/call—{ name, arguments }→{ content: [{ type: "text", text }] }ping— returns{}
Discovery:
GET https://mcp.tunnelmind.ai/
→ { service, version, protocol, transport, endpoint, tools }
Layout
src/
worker.js transport (JSON-RPC 2.0 over POST /mcp)
tools.js tool definitions + handlers
test/
tools.test.js unit tests for tool registry
Setup
npm test
npx wrangler deploy
No bindings, no secrets — this Worker is a thin proxy with no state.
Comments
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From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.