Name: Ezkielyna
Author: ezkielynagroup

Ezkielyna MCP

Ask or compare other AI models, web search and balance via the Ezkielyna API (prepaid key).

Grade A Local · stdio API key 5 tools v1.0.0 MIT

No reviews yet by ezkielynagroupnpm Runs on your machine, nothing hosted

96/100

trust score

tools declared

local

runs on your machine

—

downloads a day

What it does

Ask or compare other AI models, web search and balance via the Ezkielyna API (prepaid key).

Quickstart

# 1 — add it to Claude Code
claude mcp add --scope user --env 'EZKIELYNA_API_KEY=${EZKIELYNA_API_KEY}' --transport stdio ezkielyna-mcp '--' npx -y ezkielyna-mcp

# 2 — ask your agent for something these tools do
#   ask_model, compare_models, list_models and 2 more

It needs EZKIELYNA_API_KEY: this reads it from your environment, so export it first.

Ezkielyna costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.

Publishernot claimed

ezkielynagroup9 servers

6 categories

All 9 servers

Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.

Installation

Where are you running it?

Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Ezkielyna as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. Its scan result is on the Security tab — read the surface before you approve it.

Claude Codedeclared by this listing

This is a public server: you run it yourself and this marketplace is not in the path. You need Node.js — the current LTS (24) is the safe choice; npx comes with it. Claude Code registers it in one command; --scope user makes it available in every project. Claude Code reads EZKIELYNA_API_KEY (Ezkielyna API key (Standard or Auto group)) from your environment each time it starts the server, so the value stays out of its config: export it in your shell profile (macOS, Linux), or run setx EZKIELYNA_API_KEY … and open a new terminal (Windows). The '--' is in quotes so that PowerShell passes it on.

claude mcp add --scope user --env 'EZKIELYNA_API_KEY=${EZKIELYNA_API_KEY}' --transport stdio ezkielyna-mcp '--' npx -y ezkielyna-mcp

Reconnect, or start a new session, and the tools appear in the model’s tool list.

Free on mcprush, and it runs from its publisher’s own package: this marketplace is not in the path, so there is no key of ours to hold and no card to add.

What it asks of you

It reaches a system of yours, so it needs your own credential rather than the publisher’s: EZKIELYNA_API_KEY — Ezkielyna API key (Standard or Auto group). You set it in your own client’s config, on your machine — this marketplace never holds it.

What it writes

One config entry your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.

What you approve

5 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.

Tool surface

What the model actually sees. Descriptions are diffed on every release — see version history.

Only tools that write or reach the network

Read from its source code. A server that builds its tool list when it starts can list more tools than this.

Sends one prompt to another AI model through the Ezkielyna API and returns its answer with the tokens used, latency and

Parameter	Type	Required	Notes
prompt	string	yes	The question or task for the model (include any code or context it needs; it cannot see this conversation).
system	string	no	Optional system prompt, e.g. "You are a strict code reviewer. Answer in Indonesian."
model	string	no	Model id (default deepseek-v4.1-flash). See list_models.
max_tokens	integer	no	Maximum answer length in tokens (default …, cap …).
temperature	number	no	Optional sampling temperature (0-2). Leave empty for the model default.

Sends the same prompt to 2-4 models in parallel and returns the answers side by side with tokens, latency and estimated cost

Parameter	Type	Required	Notes
prompt	string	yes	The question or task (self-contained: the models cannot see this conversation).
models	array	yes	2-4 different model ids, e.g. ["deepseek-v4.1-flash", "glm-5.3"]. See list_models.
system	string	no	Optional system prompt sent to every model.
max_tokens	integer	no	Maximum answer length per model (default …, cap …).

Lists the models your API key can use (GET /v1/models) with public list prices (USD per 1M tokens, or per call).

Parameter	Type	Required	Notes
filter	string	no	Optional text to match in the model id or type (chat, image, video, tts, stt, embedding).

Searches the web through the Ezkielyna API (POST /v1/search) and returns 1-10 results with title, URL and a snippet.

Parameter	Type	Required	Notes
query	string	yes	Search keywords (1-400 characters).
max_results	integer	no	Number of results (1-10, default 5).
time_range	string	no	Optional: only results from the last day/week/month/year.
language	string	no	Optional language code, e.g. "id" or "en".

Shows the credit limit and usage the gateway reports for your key (OpenAI-compatible billing endpoints, USD),

No parameter schema on file.

Free

$0 forever

Every tool, no call limit
No card, and mcprush charges nothing for it
Source published under MIT
Runs on your machine — nothing of it reaches our gateway
Nothing to cap, because mcprush bills nothing

Nothing here is billable: mcprush charges nothing to install Ezkielyna or to call it, at any volume.

ATrust score 96 / 100

Release 1.0.0 · scanned 12 Nov 2026

Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.

Threat score100

Client score96

Findings0 threat · 1 capability

Capabilitymoderate

Coveragesource

Verificationrepo

Surface digest8fae8ff873fa5b74b35f2a7db2c91d6837641df8c66ac49fba8f03cec68ab4e9

Score vectorthreat 100 → client 96

Term	Level	What it prices	Points
capability-exposure	moderate	capability blast radius (moderate) — client exposure if the model is manipulated	−3
verification-discount	repo	publisher verification (public source) — no provenance, but the source is public and inspectable	−1
coverage-honesty	source	inspection depth (source) — how much of the target the scan could see	−0

score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.

What the scan could actually read

A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.

Tool surfaceread

Implementation sourceread

Package metadataread

Live transportnot available

Tools were statically extracted from the published source (5 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".

Capability — what it could do if the model were manipulated

Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. moderate is the level these add up to.

Tool	Capability tags	Why the tag was assigned
ask_model	external-sink	external-sink: declares readOnlyHint: false, openWorldHint: true
compare_models	external-sink	external-sink: declares readOnlyHint: false, openWorldHint: true
list_models	untrusted-input	untrusted-input: declares openWorldHint: true (interacts with entities outside the server)
web_search	untrusted-input	untrusted-input: keyword "fetch", declares openWorldHint: true (interacts with entities outside the server)
check_balance	untrusted-input	untrusted-input: declares openWorldHint: true (interacts with entities outside the server)

Toxic-flow graph

The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.

flow-1

Untrusted input can drive an external action even though no sensitive source is exposed.

Supply chain and provenance

Integrityfirst-seen

Surface digest8fae8ff873fa5b74

Scanned2026-11-12

This is the first scan of this surface here, so there is nothing yet to compare it against.

Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.