100+ MCP tools for AI agents: content metadata, trade intelligence, business-expertise analysis.
Dev & Codev0.2.0streamable-httpmcp.gapup.io repository
| Criterion | Points | Observed |
|---|---|---|
| reachability | 25 / 25 | HTTP 200, initialize accepted in 32ms |
| protocol | 15 / 15 | valid JSON-RPC initialize result, protocolVersion 2025-06-18, serverInfo gapup-mcp@0.2.0 |
| tooling | 35 / 35 | tools/list OK: 271 tools e.g. "content_catalog"; 271/271 described, 270/271 fully-typed schemas, median description 390 chars |
| latency | 10 / 10 | initialize round-trip 32ms |
| provenance | 15 / 15 | description present; repository linked; version 0.2.0; namespace io.github.getgapup matches endpoint/repo |
Score 100/100 · latency 32ms · 271 tools · auth: open
Claude Code:
claude mcp add --transport http mcp-knowledge https://mcp.gapup.io
Generic MCP client config:
{ "mcpServers": { "mcp-knowledge": { "type": "http", "url": "https://mcp.gapup.io" } } }
MCP Queen is a graded index, not a middleman — your agent connects directly to the server above. Check the grade and evidence first; that's the point.
Share this server: permalink https://mcpqueen.com/s/io.github.getgapup/mcp-knowledge · referral link https://mcpqueen.com/go/io.github.getgapup/mcp-knowledge (counts as “routed via the queen”).
Live badge, re-probed continuously — put it in your README:
[](https://mcpqueen.com/s/io.github.getgapup/mcp-knowledge)
Think the grade is wrong? Fix the finding the evidence shows, then the next probe cycle picks it up automatically (full cycle ≈ 3 days) — or open a dispute via the MCP endpoint.
Email alerts when the grade changes or the endpoint stops answering. Double-opt-in, one-click unwatch, free while in beta.
| When (UTC) | Grade | Score | Latency |
|---|---|---|---|
| 2026-07-14 01:30 | A | 100 | 32ms |