mcp AGENTS.md

Project instructions for Verging Labs’ MCP tools, which provide benchmarks and live information about tools used by AI agents. Some data tools use x402, a payment-based access method.

In plain words
What is it for?
Using memory-tool rankings, searching Verging Labs content, checking paid endpoints, and verifying x402 trades.
Why use it?
They explain which tools are free or paid, how to access the live services, and how authentication works.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/verginglabs/mcp/agents-md
Clone the repo
git clone --depth 1 https://github.com/verginglabs/mcp

Made for: Codex, OpenCode.

Per session 836 This file is loaded in full into every session.
When invoked 836 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00836 $0.00836
Opus 5 $0.00418 $0.00418
Sonnet 5 $0.00167 $0.00167
Haiku 4.5 $0.00084 $0.00084

Measured yesterday against content hash 4fa9766430ca, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp AGENTS.md scanned grade A with 0 findings 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 yesterday.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Verging Labs — agent reference (ships in this package so it is never training-stale)

Verging Labs publishes versioned quality benchmarks of the tools AI agents depend on, measured on simulated real work rather than self-reported claims. Rankings are free; structured machine data is pay per call over x402 (payment is the authentication: no accounts, no API keys).

Live surfaces, always current:

  • https://verginglabs.com/llms.txt — site guide. https://verginglabs.com/llms-full.txt — the whole site as markdown in one fetch.
  • Every page has a markdown twin: append .md to its path, send Accept: text/markdown, or add ?mode=agent.
  • Streamable HTTP MCP endpoint with the same tools as this package plus site search: https://verginglabs.com/mcp (manifest: https://verginglabs.com/.well-known/mcp.json).
  • OpenAPI contract: https://verginglabs.com/openapi.json. Auth model: https://verginglabs.com/auth.md.

Tools in this package

fetch_memory_index (free)

Agentic Memory Index rankings: agent memory tools scored on real multi-session work.

  • Input: { "provider"?: string } — optional name filter; omit for all rows.
  • Output: structuredContent with live, index, version, released, basis, providersTotal, and providers[] (per row: index score with confidence intervals, per-kind pass rates, failure attribution, cost per 1k successful answers, time to ready, retention where published).
  • If no release is live the payload is an explicit { "error": "NOT_YET_LIVE" }, never invented rankings.

fetch_search_index (free)

Agentic Search Index rankings: web search and retrieval tools for AI agents. Same input and output contract as fetch_memory_index.

check_x402_endpoint (paid, x402)

Full graded verdict for an x402 endpoint before an agent pays it.

  • Input: { "resource": string } — absolute https URL.
  • Output when paid: decision (allow | warn | block | unknown), score, liveness, subscores, reasons, price/payTo/chain drift.
  • Output when unpaid: { "paymentRequired": true, "rawChallenge": <the x402 payment requirements> }. Pay accepts[0] (USDC on Base) with any x402 client and retry the underlying REST call with the X-PAYMENT header, or configure your x402 client for this server's calls.
  • Price: $0.035 per call as of 2026-08-04; the 402 challenge itself is always the live price.

Read the full file on GitHub · 48 lines

Changes

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.

  1. yesterday First seen · 48 lines · 836 tokens per session scan A 4fa9766430ca

Subscribe to this mod's changes

mcp AGENTS.md is an instructions file published in the GitHub repository verginglabs/mcp (0 stars, last pushed 29d ago), licensed MIT. It adds 836 tokens to every session, about $0.0042 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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