Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/agentic-community/mcp-gateway-registrynpx agentmods add skills/agentic-community/mcp-gateway-registry/search-benchmarkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentic-community/mcp-gateway-registry/search-benchmark)<a href="https://agentmods.dev/skills/agentic-community/mcp-gateway-registry/search-benchmark"><img src="https://agentmods.dev/badge/skills/agentic-community/mcp-gateway-registry/search-benchmark/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agentic-community/mcp-gateway-registry/search-benchmark"><img src="https://agentmods.dev/badge/skills/agentic-community/mcp-gateway-registry/search-benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00075 | $0.01925 |
| Opus 5 | $0.00037 | $0.00962 |
| Sonnet 5 | $0.00015 | $0.00385 |
| Haiku 4.5 | $0.00007 | $0.00193 |
Grade A, and why
search-benchmark scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -H "Authorization: Bearer $TOKEN" "{REGISTRY_URL}/api/servers?limit=2000" > /tmp/servers.json How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search Benchmark Skill
Measure semantic search quality against a deployed AI Registry. Generates a ground truth dataset from the registry's own assets, runs queries against the live API, evaluates results using standard information retrieval metrics (NDCG@10, MRR, Recall@10), and produces a markdown report.
Prerequisites
- Registry URL - The base URL of the deployed registry (e.g.,
https://d2xl2zfuhgc4l0.cloudfront.net) - JWT Token - A valid admin token in
.tokenfile (get from "Get JWT Token" button in registry UI) - Registry must have assets indexed - At least some servers, agents, or skills registered
The .token file supports both raw JWT format and the full JSON response from the registry UI.
Input
/search-benchmark [REGISTRY_URL] [TOKEN_FILE]
- REGISTRY_URL - Base URL of the registry to benchmark (default: reads from user or uses
http://localhost) - TOKEN_FILE - Path to the token file (default:
.token)
Workflow
Step 1: Check for Existing Ground Truth
Check if a ground truth dataset already exists:
ls tests/fixtures/search_dataset/ground_truth.json 2>/dev/null
If the file exists, report how many queries it contains and ask the user: "A ground truth dataset already exists (N queries). Do you want to use it or generate a new one from this registry?"
- If use existing: skip to Step 2
- If generate new: proceed to Step 1b
Step 1b: Generate Expert Ground Truth
This is NOT a simple programmatic generation. You must deeply analyze the registry's assets and craft queries like a search expert. Follow this process:
1b.1: Fetch all assets as JSON
TOKEN=$(python3 -c "
import json
with open('{TOKEN_FILE}') as f:
raw = f.read().strip()
if raw.startswith('{'):
data = json.loads(raw)
print(data.get('tokens',{}).get('access_token') or data.get('access_token',''))
else:
print(raw.replace('Bearer ',''))
")
curl -s -H "Authorization: Bearer $TOKEN" "{REGISTRY_URL}/api/servers?limit=2000" > /tmp/servers.json
curl -s -H "Authorization: Bearer $TOKEN" "{REGISTRY_URL}/api/agents?limit=2000" > /tmp/agents.json
curl -s -H "Authorization: Bearer $TOKEN" "{REGISTRY_URL}/api/skills?limit=2000" > /tmp/skills.json
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 197 lines · 75 tokens per session scan A b8fc3196d7af
search-benchmark is a skill published in the GitHub repository agentic-community/mcp-gateway-registry (903 stars, last pushed yesterday), licensed Apache-2.0. It adds 75 tokens to every session and 1,925 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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