# Epoch Ai Models (npm · @pipeworx/mcp-epoch-ai-models)

Epoch AI — AI models database

- Trust score: 83/100 (high trust)
- Change this week: +3
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- remote · `gateway.pipeworx.io`: 63/100, [markdown](https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/epoch-ai-models-mcp.md), [page](https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/epoch-ai-models-mcp)
- npm · `@pipeworx/mcp-epoch-ai-models`: 83/100 (this document), [markdown](https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models.md), [page](https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models)

## Channel facts

- Registry: `npm`
- Package: `@pipeworx/mcp-epoch-ai-models`
- Version: `0.2.1`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-05.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - No install/post-install scripts declared.
  - No production dependencies, so there is no dependency health to assess.
- **Provenance & Transparency**: 97/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to pipeworx-io/mcp-epoch-ai-models).
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 3 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 69/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 504 tokens (~168/item across 3 items; 3 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 23/100
  - Stability observed for 7 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 4 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the Epoch Ai Models MCP server?

Epoch Ai Models runs locally as an npm package, launched with npx -y @pipeworx/mcp-epoch-ai-models. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add pipeworx-io-epoch-ai-models -- npx -y @pipeworx/mcp-epoch-ai-models
```

### Cursor

```json
{
  "mcpServers": {
    "pipeworx-io-epoch-ai-models": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-epoch-ai-models"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "pipeworx-io-epoch-ai-models": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-epoch-ai-models"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add pipeworx-io-epoch-ai-models -- npx -y @pipeworx/mcp-epoch-ai-models
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "pipeworx-io-epoch-ai-models": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@pipeworx/mcp-epoch-ai-models"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add pipeworx-io-epoch-ai-models --command npx --arg -y --arg @pipeworx/mcp-epoch-ai-models
```

### Hermes

```yaml
mcp_servers:
  pipeworx-io-epoch-ai-models:
    command: "npx"
    args: ["-y", "@pipeworx/mcp-epoch-ai-models"]
```

### Netclaw

```json
{
  "McpServers": {
    "pipeworx-io-epoch-ai-models": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "@pipeworx/mcp-epoch-ai-models"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add pipeworx-io-epoch-ai-models -t stdio -c npx -a -y @pipeworx/mcp-epoch-ai-models
```

### Other

```json
{
  "mcpServers": {
    "pipeworx-io-epoch-ai-models": {
      "command": "npx",
      "args": [
        "-y",
        "@pipeworx/mcp-epoch-ai-models"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-04 (score 83, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-02 (score 82, +1)

No change was recorded against any check on this day. Stability & Change Management went from 10 to 13. That category is still filling its 30-day observation window: 3 days of observed history at the previous scan, 4 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-01 (score 81, +1)

- [security regression] Tool safety: pass → unverified
- [security] Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- [functional regression] Tool coverage: 100 → unverified
- [functional regression] Capabilities: pass → unverified
- [functional improvement] Stability: unverified → 0.10
- [functional] First check of Schema quality: unverified
- [functional] Package version: 0.2.0 → 0.2.1

### 2026-10-30 (score 80, 0)

- [functional regression] Security disclosure: unverified → fail

### 2026-10-29 (score 80)

First indexed and scored.

## MCP tools (3)

### `ai_model` (~129 tokens)

Look up one AI model in Epoch AI's models database by name — organization, release date, parameter count, training-compute (FLOP) estimate, hardware, accessibility. Resolves dated variants (e.g. "GPT-4" matches Epoch AI's "GPT-4 (Mar 2023)" row). An unmatched name returns found:false with the closest names in the dataset, never an empty result.

Input parameters:

- `name` (string, required): Model name, e.g. "GPT-4", "Gemini 1.5 Pro", "Llama 3.1 405B"

### `ai_models_search` (~215 tokens)

Search/filter Epoch AI's models database by organization, domain (e.g. "Language", "Vision", "Multimodal"), publication year, and/or a minimum training-compute (FLOP) threshold. Returns newest-first, capped at `limit` (default 50) with count/truncated so a large match set is never silently cut.

Input parameters:

- `domain` (string): Case-insensitive substring filter on domain, e.g. "Language", "Vision", "Speech"
- `limit` (number): Max rows to return, default 50, max 200
- `min_compute` (number): Minimum training compute in FLOP, e.g. 1e25
- `offset` (number): Row offset for paging, default 0
- `organization` (string): Case-insensitive substring filter on organization name, e.g. "OpenAI"
- `query` (string): Case-insensitive substring filter on model name
- `year` (number): Restrict to models published in this calendar year

### `ai_compute_trend` (~103 tokens)

Yearly training-compute trend from Epoch AI's models database: for each year, the number of models with a compute estimate, the largest training run (FLOP) that year, and which model set it. Optionally filtered by domain and a starting year.

Input parameters:

- `domain` (string): Case-insensitive substring filter on domain, e.g. "Language"
- `from_year` (number): Earliest calendar year to include, default 2010

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models#diagnostics

## Score history

- 2026-11-05: 83
- 2026-11-04: 83
- 2026-11-03: 82
- 2026-11-02: 82
- 2026-11-01: 81
- 2026-10-31: 80
- 2026-10-30: 80
- 2026-10-29: 80

## Common questions

### What is the Epoch Ai Models MCP server?

Epoch Ai Models is an MCP server listed in the public MCP registry as io.github.pipeworx-io/epoch-ai-models. Epoch AI, AI models database. This page covers its npm package (@pipeworx/mcp-epoch-ai-models).

### Is the Epoch Ai Models MCP server safe to use?

Epoch Ai Models scores 83 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. It declares no install or post-install scripts. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Epoch Ai Models MCP server expose?

Epoch Ai Models exposes 3 tools: ai_model, ai_models_search, ai_compute_trend. Their descriptions and schemas cost roughly 447 tokens of context every time the server is loaded.

### Is the Epoch Ai Models MCP server still maintained?

Epoch Ai Models is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the Epoch Ai Models MCP server under?

Epoch Ai Models declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

### What did VerifyMCP test on the Epoch Ai Models MCP server?

VerifyMCP ran 16 checks on Epoch Ai Models, covering Malware scan, Known CVEs, Install scripts, Dependency health and 12 more. Endpoint Security and Transport & Reachability do not apply to an npm package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.

## Links

- npm package: https://www.npmjs.com/package/@pipeworx/mcp-epoch-ai-models
- Socket report: https://socket.dev/npm/package/@pipeworx/mcp-epoch-ai-models
- Repository: https://github.com/pipeworx-io/mcp-epoch-ai-models
- Website: https://pipeworx.io/packs/epoch-ai-models
- Changelog RSS feed: https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models.xml
- Changelog JSON feed: https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models/changelog.json
- Trust report (JSON): https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models.json
- HTML version of this page: https://verifymcp.io/servers/pipeworx-io-epoch-ai-models/pipeworx-mcp-epoch-ai-models