com.synqtune/mcp

Fine-tune a small model on your data and benchmark it against your LLM API, in your AWS account.

What does this entry provide?

com.synqtune/mcp is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 100/100. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding com.synqtune/mcp to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.

Snapshot facts

Source: Official MCP Registry
Quality: 100/100
Install method: pypi
Repo: Registry only
Repo updated: Nov 1, 2026

Install command

uvx synqtune-mcp==0.1.5

Install method: pypi

Review the upstream source before running this command.

Source entry

Quality

100

Repo stars

Repo updated

Nov 1, 2026

How is this score calculated?

Weighted across six dimensions, scored 0-100.
Provenance (25): listed in an official or curated registry.
Installability (25): a runnable install command beats a declared transport, which beats a source checkout.
Maintenance (20): recency of the last push; archived entries score zero here.
Adoption (20): repository stars on a log curve.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-11-01T17:21:58.60604Z",
      "publishedAt": "2026-11-01T17:21:58.60604Z",
      "statusChangedAt": "2026-11-01T17:21:58.60604Z"
    }
  },
  "server": {
    "name": "com.synqtune/mcp",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "0.1.5",
    "packages": [
      {
        "version": "0.1.5",
        "transport": {
          "type": "stdio"
        },
        "identifier": "synqtune-mcp",
        "registryType": "pypi",
        "environmentVariables": [
          {
            "name": "SYNQTUNE_API_TOKEN",
            "isSecret": true,
            "isRequired": true,
            "description": "Token from Agent access in SynqTune. Read-only unless created with Can launch runs."
          },
          {
            "name": "SYNQTUNE_URL",
            "description": "SynqTune address. Defaults to https://synqtune.com."
          }
        ]
      }
    ],
    "description": "Fine-tune a small model on your data and benchmark it against your LLM API, in your AWS account."
  }
}

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