temsor API
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MCP Tool Surface Index

Searchable, dated archive of what every public MCP server actually exposes — tool definitions, daily change feed, and rug-pull detection.

POST /v1/mcp/index · 1 credit

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POST/v1/mcp/index 
{
  "view": "search",
  "q": "invoice"
}
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1endpoints
—data points banked
—time series
—median response

Why this exists

Built for hostile input

A Turkish address arrives as "Cd." or "Cad." or "Caddesi", with the flat number glued to the building number. Generic parsers drop half of it silently. This one tells you what it could not place.

Every number carries its provenance

Each archived point stores the source URL and a content hash of the page it came from, and the archive is committed to a Merkle root anchored in Bitcoin. Every commitment — with its cutoff, leaf count and anchors — is published at /proof, so you can check for yourself how current the latest one is. The bulletins themselves are public and anyone can read them; what this adds is that a number you quote can be shown to be the number we held on that date, and that it has not been edited since.

You only pay for work

Repeated inputs come from cache and cost zero credits. If a response ever fails its own schema, the call is refunded automatically.

Endpointsexpand any row to see the parameters and call it live

AI Infrastructure1

/v1/mcp/index MCP Tool Surface Index 1 credit

Searchable, dated archive of what every public MCP server actually exposes — tool definitions, daily change feed, and rug-pull detection.

The official MCP registry publishes a server’s name and address but not its tool surface; the only way to learn what a server exposes is to connect and call `tools/list`. This endpoint does that daily across every public remote server and keeps the result. Three things become answerable that the source cannot answer: tool-level search (the registry has none), uptime, and — the one that matters for security — what a tool’s description said yesterday. In MCP a tool description is part of the context handed to the model, so it is prompt text; if it changes after the user approved the server, the server has silently injected new instructions. Each indexed tool also carries a review score with the matched evidence, so the claim can be checked rather than trusted. Measurement boundary: only `initialize` and `tools/list` are ever called — never `tools/call`.

Parameters

view "search" | "changes" | "server" | "tool" | "stats" `search`: araç adı/açıklamasında ara · `changes`: değişim akışı (asıl ürün) · `server`: bir sunucunun gün gün ölçüm tarihçesi · `tool`: bir aracın tanım tarihçesi · `stats`: endeksin kendi ölçüsü. default "search"
q string Arama terimi (yalnız `search`), ör. `invoice`, `calendar`, `sql`.
server string Kayıt defteri sunucu adı, ör. `com.temsor/api`. `server`/`tool` görünümlerinde zorunlu.
tool string Araç adı (yalnız `tool` görünümü).
minRisk integer Yalnız inceleme puanı bu değerin üstündeki araçlar (yalnız `search`).
severity "high" | "medium" | "low" | "info" Yalnız `changes`.
type string Olay türü süzgeci (yalnız `changes`), ör. `tool_description_changed`.
days integer Kaç günlük pencere (`changes` ve `server`). default 30
limit integer default 50
POST/v1/mcp/index 
{
  "view": "search",
  "q": "invoice"
}
no request sent yet
Press Run to call the live API from your browser.

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Credits are consumed per call and cache hits are free. Requests without a key run on a narrow per-IP demo quota so you can evaluate before signing up.

The API key is e-mailed the moment payment clears. Upgrades keep the same key, so your integration is never broken.

Want to finish the integration before paying?

Use it from an AI assistantthe same catalogue, exposed as MCP tools

Every endpoint is also published over the Model Context Protocol, so Claude, ChatGPT or your own agent can call it directly — no glue code, no wrapper functions. The assistant sees the same input schemas and the same metering.

Currently 25 tools. New endpoints appear automatically; nothing to update on your side.

claude_desktop_config.json

{
  "mcpServers": {
    "temsor": {
      "url": "https://api.temsor.com/mcp",
      "headers": { "x-api-key": "fk_live_…" }
    }
  }
}

Quickstart

Official client: npm install temsor-api · npmjs.com/package/temsor-api

Node.js

import Client from "temsor-api";

const api = new Client({ apiKey: KEY });
const r = await api.${(() => {
  const first = apis[0];
  return first.slug.split(/[/-]/).map((p, i) => (i === 0 ? p : p[0].toUpperCase() + p.slice(1))).join('');
})()}(${esc(JSON.stringify(apis[0].examples[0]?.input ?? {}))});
console.log(r, r.$meta);

cURL

curl -s https://api.temsor.com/v1/mcp/index \
  -H "content-type: application/json" \
  -H "x-api-key: fk_live_…" \
  -d '{"view":"search","q":"invoice"}'

JavaScript

const res = await fetch("https://api.temsor.com/v1/mcp/index", {
  method: "POST",
  headers: { "content-type": "application/json", "x-api-key": KEY },
  body: JSON.stringify({"view":"search","q":"invoice"})
});
const { data } = await res.json();

Python

import httpx
r = httpx.post("https://api.temsor.com/v1/mcp/index",
    headers={"x-api-key": KEY},
    json={"view":"search","q":"invoice"})
data = r.json()["data"]