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PopNx MCPMCP servers for people who use AI · explained in plain words

Embedbase

by CloudCorpRecordsversion 0.1.0i★ –iRuns on your computer
Registry nameio.github.CloudCorpRecords/embedbase

Install

Overview

Description from the maker (original English)

Vector collections and document search backed by a Chroma HTTP service.

PopNx MCP’s three pillars

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

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: Search & AI memory

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).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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": {
    "embedbase": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/embedbase",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add embedbase -- npx -y @reneturcios/embedbase mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "embedbase": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/embedbase",
        "mcp"
      ]
    }
  }
}

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": {
    "embedbase": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/embedbase",
        "mcp"
      ]
    }
  }
}

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.

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 CloudCorpRecords, 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 Search & AI memoryi

  • More stars than 0% of the other 7251 servers in this category
  • Published to the registry more recently than 84% of the other 7251 servers in this category
  • Basic checks equal to or better than 100% of the other 7251 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 Embedbase 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?

The registry does not list a required key, though some servers ask you to sign in on first use.

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 (0.1.0) reached the registry 7 days ago.

Which apps can use it?

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

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today
Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago
Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month
Install

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.

embedbase

embedbase gives an agent — or you, at a terminal — a tidy way to work with vector collections: create them, fill them with documents, and query them for the closest matches. It speaks to a Chroma-compatible HTTP service over its v2 REST API, so the embedding store stays a separate process and this tool stays a thin, testable client.

Point it at a running service with CHROMA_URL or EMBEDBASE_URL (without either, it assumes http://localhost:8000). Collections are addressed by name at the MCP and CLI layers; internally the client resolves each name to its server id before calling the id-scoped document endpoints, exactly as the REST API requires.

Install

npx @reneturcios/embedbase list

Or run the container image:

docker run -i ghcr.io/cloudcorprecords/embedbase

The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead.

CLI

# List collections (pagination is optional)

embedbase list --limit 20 --offset 0

Inspect one collection, or count its records

embedbase info notes embedbase count notes

Create a collection

embedbase create notes

Start the MCP server

embedbase mcp

embedbase --version

Exit codes: 0 on success, 1 when the service call fails (the error includes the HTTP status), 2 for usage errors.

MCP server

One bin serves both faces. The mcp subcommand starts a stdio MCP server:

npx -y @reneturcios/embedbase mcp

MCP client configuration:

{

"mcpServers": { "embedbase": { "command": "npx", "args": ["-y", "@reneturcios/embedbase", "mcp"], "env": { "CHROMA_URL": "http://localhost:8000" } } } }

Tools

All tools take collection_name (string) unless noted. Optional parameters are omitted from the request when not supplied.

ToolRequiredOptionalPurpose
chroma_list_collections—limit, offset (integers)List collections with pagination.
chroma_create_collectioncollection_namemetadata (object), embedding_function_name (string)Create a collection.
chroma_peek_collectioncollection_namelimit (integer)Preview documents in a collection.
chroma_get_collection_infocollection_name—Collection metadata and configuration.
chroma_get_collection_countcollection_name—Number of records in a collection.
chroma_modify_collectioncollection_namenew_name, new_metadataRename or re-tag a collection.
chroma_delete_collectioncollection_name—Delete a collection and its records.
chroma_add_documentscollection_name, documents (string array)metadatas, idsAdd documents; ids are generated deterministically when omitted.
chroma_query_documentscollection_name, query_texts (string array)n_results, where, where_document, includeNearest-neighbour query.
chroma_get_documentscollection_nameids, where, limit, offset, includeFetch documents by id or filter.
chroma_update_documentscollection_name, idsdocuments, metadatas, embeddingsUpdate existing records.
chroma_delete_documentscollection_nameids, whereDelete records by id or filter.

Requests go to the v2 tenant/database paths (/api/v2/tenants/default_tenant/databases/default_database/collections...). Service errors come back as tool errors carrying the HTTP status — results are never invented.

Development

npm install

npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, fake fetch only, no live service npm run dev # run the CLI from source via tsx

The client core sits behind an injectable fetch function, which is what the test suite drives: URL construction, request bodies, id resolution, count unwrapping, and error surfacing are all covered without a running server.

License

MIT — see LICENSE.

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