Multiplayer mode for AI coding agents: team huddles, master prompt, task board, file claims.
The Neural Net is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
What it does
Sourced register of open-weight AI model releases and AI news. Every field cites its source.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http the-neural-net-mcp https://theneuralnet.com/api/mcp
# 2 — ask your agent for something these tools do
# search_models, get_model, recent_releases and 3 more
The Neural Net costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http the-neural-net-mcp https://theneuralnet.com/api/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
6 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.
Search the model register: open-weight AI model releases with exact parameter counts, architectural context length, licence and release date. Use this to answer questions about which models exist, how big they are, what they are licensed under, or what shipped recently.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| organisation | string | no | e.g. qwen, deepseek-ai, meta-llama, google |
| license | string | no | e.g. apache-2.0, mit |
| task | string | no | e.g. text-generation, image-text-to-text, mask-generation |
| min_parameters | number | no | Minimum parameter count, e.g. 7000000000 |
| max_parameters | number | no | — |
| min_context | number | no | Minimum architectural context length in tokens |
| tool_calling | boolean | no | Only models whose chat template shows tool-calling support |
| reasoning | boolean | no | Only models whose chat template shows reasoning/thinking support |
| image_input | boolean | no | Only models that accept image input |
| released_after | string | no | ISO date, e.g. 2026-01-01 |
| query | string | no | Substring match on the model id |
| include_derivatives | boolean | no | Include quantisations and conversions of other releases (GGUF, MLX, AWQ and similar). Default false. |
| limit | number | no | Default 25, max 100 |
Get the full record for one model, including every field and the endpoint each field was sourced from. Use when you need provenance or complete detail.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| id | string | yes | Repo id, e.g. "Qwen/Qwen3.8-27B" |
Models first recorded in the register within the last N days. Use to answer 'what shipped recently' or 'what is new in open-weight models'.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| days | number | no | Look-back window, default 30 |
| limit | number | no | Default 25 |
Summary of what the register covers: how many models, field coverage, organisations tracked, and the inclusion rule. Use to judge whether the register can answer a question before querying it.
No parameter schema on file.
Search stories published by The Neural Net. Each story is written from a primary source and links to it. Use for narrative context on a release rather than raw model facts.
| Parameter | Type | Required | Notes |
|---|---|---|---|
| query | string | no | Substring match on headline and summary |
| topic | string | no | e.g. models, products, infrastructure, research, policy, safety |
| limit | number | no | Default 10 |
Everything The Neural Net harvested in the last day that it did not write up, grouped by source and linked to the original. Use for a broad view of current activity.
No parameter schema on file.
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install The Neural Net or to call it, at any volume.
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.
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | minimal | capability blast radius (minimal) — client exposure if the model is manipulated | −0 |
| coverage-honesty | manifest | inspection depth (manifest) — how much of the target the scan could see | −4 |
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.
The scan read each tool’s name, description, input schema and annotations exactly as the server listed them the last time it answered us; no code was reviewed. We ask the server again about once a month, and a list that changed is graded again.
The implementation source was not read — this reflects the declared tool metadata only.
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. minimal is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| search_models | no tags | |
| get_model | no tags | |
| recent_releases | no tags | |
| register_stats | no tags | |
| search_news | no tags | |
| get_wire | no tags |
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.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
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.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.0.0.
No release note was published with this version.
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Any signed-in account that does not publish The Neural Net can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.