# agmind-mcp

> agmind-mcp — botagi-agmind-mcp. Use this tool when you need to access and analyze benchmark claims for local large language models (LLMs) on specific hardware configurations, such as AMD Strix Halo and DGX Spark. It provides read-only access to measured claims like throughput, latency, and task success rates via search, lookup, and listing tools. This tool is ideal for evaluating and comparing LLM performance on different hardware setups.

Canonical page: https://skillsregistry.net/skills/botagi-agmind-mcp  
JSON: https://api.skillsregistry.net/v1/skills/botagi-agmind-mcp

## Description

Read-only MCP server exposing AGmind Systems Lab's measured local-LLM benchmark claims (TTFT, inter-token latency, task success, etc.) on AMD Strix Halo and DGX Spark hardware via search, claim lookup, and measured-combination listing tools.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-04

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-04

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/lshr68tgjw)
- **Repository:** <https://github.com/botAGI/agmind-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "botagi-agmind-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/botagi-agmind-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/botagi-agmind-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt