Gemdex

Persistent memory layer for AI coding agents: save, recall, update via Gemini plus LanceDB

What does this entry provide?

Gemdex is an MCP server entry in ChatHome Skills, sourced from Official MCP Registry and scored 73/100. 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 Gemdex 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: 73/100
Install method: npm
Repo: nikships/gemdex
Repo updated: Sep 23, 2026

Install command

npx -y gemdex-mcp@1.0.47

Install method: npm

Review the upstream source before running this command.

GitHub project

Quality

Repo stars

Repo updated

Sep 23, 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.
Documentation (10) and description quality (10): parsed manifest or SKILL.md frontmatter, and a real description rather than a placeholder.

MCP manifest

{
  "_meta": {
    "io.modelcontextprotocol.registry/official": {
      "status": "active",
      "isLatest": true,
      "updatedAt": "2026-09-23T10:26:06.975218Z",
      "publishedAt": "2026-09-23T10:26:06.975218Z",
      "statusChangedAt": "2026-09-23T10:26:06.975218Z"
    }
  },
  "server": {
    "name": "io.github.nikships/gemdex",
    "title": "Gemdex",
    "$schema": "https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json",
    "version": "1.0.47",
    "packages": [
      {
        "version": "1.0.47",
        "transport": {
          "type": "stdio"
        },
        "identifier": "gemdex-mcp",
        "runtimeHint": "npx",
        "registryType": "npm",
        "runtimeArguments": [
          {
            "type": "positional",
            "value": "-y",
            "valueHint": "auto-confirm install"
          },
          {
            "type": "positional",
            "value": "gemdex-mcp@1.0.47",
            "valueHint": "package spec"
          }
        ],
        "environmentVariables": [
          {
            "name": "GEMINI_API_KEY",
            "format": "string",
            "isSecret": true,
            "isRequired": true,
            "description": "Google AI Studio key for local mode, or the exact value 'local' for on-device MLX text embeddings. Not needed in remote mode."
          },
          {
            "name": "GEMDEX_MODE",
            "format": "string",
            "choices": [
              "local",
              "remote"
            ],
            "default": "local",
            "description": "Memory backend: embedded local LanceDB or a self-hosted Gemdex Server"
          },
          {
            "name": "LANCEDB_PATH",
            "format": "filepath",
            "default": "~/.gemdex/lance",
            "description": "Directory for the embedded LanceDB store"
          },
          {
            "name": "EMBEDDING_MODEL",
            "format": "string",
            "choices": [
              "gemini-embedding-2",
              "gemini-embedding-001"
            ],
            "default": "gemini-embedding-2",
            "description": "Gemini text embedding model"
          },
          {
            "name": "GEMDEX_REMOTE_URL",
            "format": "string",
            "description": "Gemdex Server root URL (required in remote mode)"
          },
          {
            "name": "GEMDEX_REMOTE_TOKEN",
            "format": "string",
            "isSecret": true,
            "description": "Gemdex Server bearer token (required in remote mode)"
          },
          {
            "name": "GEMDEX_REMOTE_NAME",
            "format": "string",
            "description": "Human-readable name for the remote server"
          },
          {
            "name": "GEMDEX_TRUST_RANKING",
            "format": "boolean",
            "default": "false",
            "description": "Re-rank recall results by recorded worked/failed/stale outcomes"
          }
        ]
      }
    ],
    "repository": {
      "id": "1249655672",
      "url": "https://github.com/nikships/gemdex",
      "source": "github"
    },
    "websiteUrl": "https://github.com/nikships/gemdex",
    "description": "Persistent memory layer for AI coding agents: save, recall, update via Gemini plus LanceDB"
  }
}

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