AI infrastructure & agent explorers

MCP Server Explorer

Inspect any MCP server before you connect an AI agent: tools, permissions, risks, changes over time.

Stores a hash of the URL and per-tool hashes only.

Try an example: Mixed-risk server (offline)

How it works

Connects to a remote Model Context Protocol server (current stateless 2026-07-28 protocol or the classic initialize handshake, JSON or SSE responses), lists its tools, resources and prompts, and classifies every tool: capabilities (read, write, delete, execute, network, files, payments, messaging, secrets), annotation consistency, schema quality and tool-poisoning markers. It remembers a fingerprint per server so later checks show added, removed and silently changed tools. You can also paste a tools/list result or search the official MCP Registry.

  • Connect: POST server/discover (MCP 2026-07-28, stateless, with MCP-Protocol-Version and Mcp-Method headers); if unsupported, the classic initialize → notifications/initialized handshake (2025-11-25) with Mcp-Session-Id. JSON and SSE responses are both parsed. tools/list, resources/list and prompts/list are paginated up to 5 pages.
  • Capabilities are inferred from the tool name (write/delete/execute) and name + description (network, files, payments, messaging, secrets). Risk: high = delete/execute/payment, destructiveHint=true or poisoning markers; medium = write/messaging/secrets/open-world network; otherwise low.
  • Issues: annotations contradicting the name, missing annotations, missing descriptions, undocumented input properties, and text patterns typical of tool-poisoning (hidden instructions, references to ~/.ssh or .env, "do not tell the user").
  • Changes: with "remember", per-tool SHA-256 fingerprints of description + input schema + annotations are stored under a hash of the URL; the next check lists added, removed and changed tools (a changed description is how "rug-pull" attacks work).
  • Registry: GET registry.modelcontextprotocol.io/v0/servers?search=…

For scripts and AI agents

  • JSON API: POST https://mcpserverexplorer.usefulweb.site/api/v1/calculate (same calculation as this page)
  • Interface description: OpenAPI 3.1 · AI guide: llms.txt
  • MCP server (Streamable HTTP): https://mcpserverexplorer.usefulweb.site/mcp · tool name mcp_server_explorer
Example request
curl -s -X POST https://mcpserverexplorer.usefulweb.site/api/v1/calculate \
  -H 'content-type: application/json' \
  -d '{…see OpenAPI examples…}'

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