Topic Scorer is listed as active in the registry but did not answer our last check. It exposes 5 tools.
Score pages against 11,485 public taxonomy categories by embedding similarity. Free.
The linked repository no longer exists on GitHub — it was deleted or made private.
Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 4 November 2026. No other catalogue keeps this.
Over the last week it answered 29.3% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.
Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 3 min ago.
claude mcp add topic-scorer --transport http https://topic-scorer.pixelcove.co/mcp
https://topic-scorer.pixelcove.co/mcp
[mcp_servers.topic-scorer]
url = "https://topic-scorer.pixelcove.co/mcp"
{
"mcpServers": {
"topic-scorer": {
"url": "https://topic-scorer.pixelcove.co/mcp"
}
}
}
{
"servers": {
"topic-scorer": {
"type": "http",
"url": "https://topic-scorer.pixelcove.co/mcp"
}
}
}
Read directly from the server with tools/list, grouped by what they act on.
If a tool disappears, we record the date.
topic_scorer_find
topic_scorer_gate
topic_scorer_phrases
topic_scorer_score
topic_scorer_taxonomies
| URL | Transport | State | Latency | Checked |
|---|---|---|---|---|
| https://topic-scorer.pixelcove.co/mcp | streamable-http | answering | 19 ms | 3 min ago |
33 tools: LLM chat, summaries, translation, embeddings, speech, images. 25 free calls.
Create and edit PDFs: text, Markdown, tables, metadata and pages, with Japanese font embedding.
Local-first memory for coding agents — MCP server, single SQLite file, local embeddings
x402-gated semantic vector cache for agent swarms: Redis-backed similarity lookup. Paid in USDC.
Store and retrieve text in a Qdrant vector database by similarity search.
Agent-operated. Free LLM, GPU, search and embedding API tiers: limits, dated, linked to the source.
RAG memory for LLM agents over Garnet Vector Sets: store text as embeddings, recall by meaning.
BM25 search + tree navigation over markdown docs for AI agents. No embeddings, no LLM calls.
Answers built from our own checks of this server.