Gemdex

Name: Gemdex
Author: nikships

by nikshipsversion 1.0.47i★ –iRuns on your computer

Registry nameio.github.nikships/gemdex

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Developer tools
You need to fill in: GEMINI_API_KEY, GEMDEX_REMOTE_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: GEMINI_API_KEY, GEMDEX_MODE, LANCEDB_PATH, EMBEDDING_MODEL, GEMDEX_REMOTE_URL, GEMDEX_REMOTE_TOKEN, GEMDEX_REMOTE_NAME, GEMDEX_TRUST_RANKING

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "gemdex": {
      "command": "npx",
      "args": [
        "-y",
        "gemdex-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value",
        "GEMDEX_MODE": "your-value",
        "LANCEDB_PATH": "your-value",
        "EMBEDDING_MODEL": "your-value",
        "GEMDEX_REMOTE_URL": "your-value",
        "GEMDEX_REMOTE_TOKEN": "your-value",
        "GEMDEX_REMOTE_NAME": "your-value",
        "GEMDEX_TRUST_RANKING": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add gemdex --env GEMINI_API_KEY=your-value --env GEMDEX_MODE=your-value --env LANCEDB_PATH=your-value --env EMBEDDING_MODEL=your-value --env GEMDEX_REMOTE_URL=your-value --env GEMDEX_REMOTE_TOKEN=your-value --env GEMDEX_REMOTE_NAME=your-value --env GEMDEX_TRUST_RANKING=your-value -- npx -y gemdex-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "gemdex": {
      "command": "npx",
      "args": [
        "-y",
        "gemdex-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value",
        "GEMDEX_MODE": "your-value",
        "LANCEDB_PATH": "your-value",
        "EMBEDDING_MODEL": "your-value",
        "GEMDEX_REMOTE_URL": "your-value",
        "GEMDEX_REMOTE_TOKEN": "your-value",
        "GEMDEX_REMOTE_NAME": "your-value",
        "GEMDEX_TRUST_RANKING": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "gemdex": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "gemdex-mcp"
      ],
      "env": {
        "GEMINI_API_KEY": "your-value",
        "GEMDEX_MODE": "your-value",
        "LANCEDB_PATH": "your-value",
        "EMBEDDING_MODEL": "your-value",
        "GEMDEX_REMOTE_URL": "your-value",
        "GEMDEX_REMOTE_TOKEN": "your-value",
        "GEMDEX_REMOTE_NAME": "your-value",
        "GEMDEX_TRUST_RANKING": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

GEMINI_API_KEY secret required env
Google AI Studio key for local mode, or the exact value 'local' for on-device MLX text embeddings. Not needed in remote mode.
GEMDEX_MODE env
Memory backend: embedded local LanceDB or a self-hosted Gemdex Server
LANCEDB_PATH env
Directory for the embedded LanceDB store
EMBEDDING_MODEL env
Gemini text embedding model
GEMDEX_REMOTE_URL env
Gemdex Server root URL (required in remote mode)
GEMDEX_REMOTE_TOKEN secret env
Gemdex Server bearer token (required in remote mode)
GEMDEX_REMOTE_NAME env
Human-readable name for the remote server
GEMDEX_TRUST_RANKING env
Re-rank recall results by recorded worked/failed/stale outcomes

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account nikships, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

More stars than 0% of the other 4900 servers in this category
Published to the registry more recently than 50% of the other 4900 servers in this category
Basic checks equal to or better than 100% of the other 4900 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Gemdex safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GEMINI_API_KEY, GEMDEX_REMOTE_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.47) reached the registry last month.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Persistent memory for AI coding agents

Save a useful memory once and recall it across repos and sessions. Gemdex indexes small chunks for precise hybrid semantic + BM25 matching, then resolves matches to whole parent memories. MCP agents scan a cheap title index and open only the memories they need.

Two ways to run it

	Local	Self-hosted
Agent connection	`npx gemdex-mcp`, stdio	Streamable HTTP `/mcp`
Embeddings	On-device EmbeddingGemma 2 via MLX	Server-owned Gemini, including multimodal
Storage	LanceDB and blobs under `~/.gemdex`	Postgres/pgvector and file/S3 blobs
Platform	Apple Silicon, macOS 14+, native arm64 Node ≥24	Docker host
Human management	Native macOS app via localhost sidecar	Web manager
Pool	One per machine	Shared across machines
MCP tools	Seven, including delete	Six, without delete

These are separate pools. The npx package and desktop sidecar are local-only; connect directly to HTTP MCP for a self-hosted pool.

Local quickstart

npx gemdex-mcp install

claude mcp add gemdex -- npx -y gemdex-mcp@latest

The explicit install downloads managed Python/MLX and pinned mlx-community/embeddinggemma-2-8bit weights, about 1.45 GB to download and 1.9 GB on disk. No Python, uv, Homebrew, HF CLI, or compiler setup is needed. Embeddings run offline after installation. There is no API key, sentinel value, or provider switch. Rosetta Node is unsupported. See MLX model and runtime requirements.

All seven tools remain discoverable before installation and return setup guidance. Retry a tool after installation, or reconnect your MCP client.

For another MCP client:

"mcpServers": { "gemdex": { "command": "npx", "args": ["-y", "gemdex-mcp@latest"] } } }

Save and recall

Ask your agent to save something durable:

Save how we set up the review workflow to memory.

Then, in another session or repo using that pool:

Check memory for our review workflow and use it here.

Tell your agent when to use memory in its instructions:

## Memory

Use Gemdex recall to find relevant memories before starting work. Save reusable findings and update existing memories when correcting them. Report worked/failed/stale outcomes after acting on a fetched memory. Use read_attachment for transcript bytes. Delete only when a memory should be permanently removed and the connected surface provides delete_memory.

MCP tools

Tool	Behavior
`save_memory`	Save content and/or attachments (images, audio, video, text files); return id and title
`recall`	Text query and/or example media files, top 10 titles + ids, never full bodies
`get_memory`	Full parent body, age, attachments and track record
`update_memory`	Full `content` replacement or literal `edits`, optional title/attachments
`report_outcome`	Record `worked`, `failed`, or `stale`, with optional note
`read_attachment`	Attachment as UTF-8 text, a viewable image, or base64
`delete_memory`	Stdio only, permanent delete and client-stat cleanup

get_memory, not title-index recall, increments recall counts. Stats live in a separate ledger (~/.gemdex/stats.json by default). GEMDEX_TRUST_RANKING=true enables outcome-weighted title ranking; otherwise ranking is relevance-only.

Local saves include an advisory when existing memories are similar, using already-computed vectors and centroid similarity (default threshold 0.93). The advisory does not block the save. Configure it with GEMDEX_SIMILAR_ON_SAVE and GEMDEX_SIMILAR_THRESHOLD.

Attachments

Local memories can carry images (PNG, JPEG, WebP, GIF), audio (WAV, MP3, M4A, FLAC, AAC, AIFF; up to 5 minutes) and video (MP4, MOV, M4V, WebM). EmbeddingGemma 2 embeds each file on-device into the same space as text, so the memory is found by what the image shows or the recording says. Recall also takes example files: "is there anything in memory about this screenshot?" works with or without a text query. Captions are optional; they add keyword matching and help most for audio. Text files (.txt, .json, .jsonl/.ndjson) are stored as non-embedded blobs. Per memory: 8 images, 4 audio files, 2 videos and 4 text files, 100 MiB each. PDFs are not supported locally. Use a local path or inline base64 data + mimeType; every attachment is readable through read_attachment.

The self-hosted server supports Gemini multimodal embedding and media recall through /v1. HTTP MCP attachment inputs are inline base64 only, never client filesystem paths. See the /v1 contract.

Chat history and memory hygiene

Local digestion and hygiene use your existing Claude Code login. Install Claude Code and run claude auth login, then:

npx gemdex-mcp status

npx gemdex-mcp ingest-history --source claude --dry-run npx gemdex-mcp ingest-history --source claude

Sources include Claude Code, Factory CLI, Codex, Antigravity, or a folder path. Only never-before-ingested sessions are processed. Each produces a digest memory and a cleaned transcript attachment. backfill-transcripts attaches files referenced by older digest footers, with --dry-run and --force options; missing files are skipped with a message.

Inference runs as isolated claude -p --model haiku structured-JSON calls: no tools, settings, skills, MCP servers, hooks, CLAUDE.md, or session persistence, and a temporary working directory. Concurrency is four, with at most three total attempts and a five-minute timeout per call.

Cost estimates are Haiku API list-price equivalents ($1 input / $5 output per million tokens). With a Claude subscription, usage counts against plan limits, not a per-token bill. Local embeddings stay on-device, but ingestion transcripts and hygiene candidates go through Claude Code inference.

Hygiene first clusters local vectors, then judges candidates with Claude Code. Deleting findings requires human approval. Self-hosted uploads instead use the server's Gemini digestion. See chat-history paths.

The desktop app

The native macOS app manages the local pool: browse, search (by text or by file), and edit memories, attach and preview images, audio and video, ingest chat history, and review hygiene findings. It talks to gemdex serve, which binds only 127.0.0.1 and uses a per-launch token. Its contract exposes explicit MLX install/migration jobs and Claude Code readiness. Memory routes return 503 {needsInstall:true} until installation; ingestion/hygiene start requires Claude Code readiness. See the sidecar contract.

The web manager is the primary human surface for self-hosted deployments. The desktop app is not a client for that pool.

Self-host the whole stack (one command)

curl -fsSL https://raw.githubusercontent.com/nikships/gemdex/main/scripts/install.sh | bash

The installer starts Postgres, gemdex-server, HTTP MCP and the web manager, generates secrets, waits for migrations, verifies a real save and recall, and prints Streamable HTTP client configuration. It asks for a Google AI Studio key, or reads GEMINI_API_KEY. This key belongs to the server, not the agent client.

The default is loopback-only. --lan exposes MCP and web to your trusted LAN with static MCP auth and login-free web access. For public access, use HTTPS, Google OAuth, and the deployment guide. Never publish Postgres or /v1.

"mcpServers": { "gemdex": { "type": "http", "url": "https://gemdex.example.com/mcp" } } }

This example targets a Google OAuth deployment; the client handles login.

Guide	Purpose
Self-host deploy	Compose, Google OAuth, HTTPS edge and exposure checks
Operations	Storage, backup/restore, upgrades and troubleshooting
Go further	DNS, managed platforms, sizing and costs
Security	Enforced boundaries and pre-launch checklist
Chat history	Local ingestion, web upload and OAuth record import

Packages and library use

Package	Responsibility
core	MemoryStore, embedding providers, shared HTTP router and inference
mcp	Local stdio tools, CLI and desktop sidecar
server	BYOI `/v1`, Postgres/pgvector, Gemini and file/S3 blobs
mcp-http	Six-tool Streamable HTTP agent surface
web	Browser manager and session-upload BFF
app	Native local manager

To use the engine directly, see the core library example. Local environment settings are in the MCP README; self-hosted settings are in the server README.

Privacy & safety

Memory text and attachment bytes are plaintext unless you add your own storage controls. Gemdex provides no secret redaction or hosted custody service. Local embeddings run on-device; local ingestion and hygiene send selected content through Claude Code using your account. The self-hosted server sends embedding payloads and uploaded-session digestion to Gemini using its key. See custody and self-host security.

Build from source

From a clone with Node ≥24 and pnpm ≥10:

pnpm install

pnpm build

The local MCP entry point is packages/mcp/dist/index.js. See CONTRIBUTING.md for checks and development guidance.

License

MIT. See LICENSE.

MCP Registry

mcp-name: io.github.nikships/gemdex

Gemdex

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Developer toolsi

Common questions

Alternatives

GitHub

Desktop Commander

Cloudflare MCP

README from the maker

Persistent memory for AI coding agents

Two ways to run it

Local quickstart

Save and recall

MCP tools

Attachments

Chat history and memory hygiene

The desktop app

Self-host the whole stack (one command)

Packages and library use

Privacy & safety

Build from source

License

MCP Registry