MCP Servers
ArcadeData/arcadedb
ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS.
Our verdict
We have not reviewed ArcadeData/arcadedb yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About ArcadeData/arcadedb
ArcadeDB is a multi-model database management system that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB, and Redis APIs. It is a conceptual fork of OrientDB and includes support for vector embeddings. The database is written in Java and is available as open source on GitHub.
Best for
Developers who need a flexible multi-model database with vector capabilities and want to avoid managing separate systems
Use cases
- Build applications that require graph, document, and key-value models in a single database
- Use as a vector database for similarity search and AI workflows
- Migrate from OrientDB to a maintained fork with extended features
Notes
909 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.
Pros
- Supports multiple query languages and APIs, reducing integration complexity
- Includes native vector embedding support for modern AI use cases
- Open source with an active GitHub repository
Cons
- Smaller community and ecosystem compared to established databases like PostgreSQL or MongoDB
- Java runtime dependency may not suit all deployment environments
- As a fork, documentation and third-party tooling may be less mature
Key facts
What we have checked
- Days since the last commit
- 0
- GitHub forks
- 160
- GitHub stars
- 1,220
- Open issues
- 140
- Releases in the last 90 days
- 4
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
How to use
How to set it up
As the listing publishes it. We have not run this install.
Tools exposed
ArcadeDB
Install
Add ArcadeData/arcadedb to your client
Our lab has not run this server yet. "Config checked" on a client means the recipe matches that client's documented config format; it does not mean we ran it.
Claude Code
Config checkedRun in your terminal (runs on your computer)
claude mcp add --transport stdio arcadedata-arcadedb -- docker run -i --rm docker.io/arcadedata/arcadedb:26.4.1-SNAPSHOTClaude Desktop
Config checkedAdd to claude_desktop_config.json (runs on your computer)
{
"mcpServers": {
"arcadedata-arcadedb": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/arcadedata/arcadedb:26.4.1-SNAPSHOT"
]
}
}
}Cursor
Config checkedAdd to .cursor/mcp.json (runs on your computer)
{
"mcpServers": {
"arcadedata-arcadedb": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/arcadedata/arcadedb:26.4.1-SNAPSHOT"
]
}
}
}VS Code
Config checkedAdd to .vscode/mcp.json (runs on your computer)
{
"servers": {
"arcadedata-arcadedb": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"docker.io/arcadedata/arcadedb:26.4.1-SNAPSHOT"
]
}
}
}Codex
Config checkedAdd to ~/.codex/config.toml (runs on your computer)
[mcp_servers.arcadedata-arcadedb]
command = "docker"
args = ["run", "-i", "--rm", "docker.io/arcadedata/arcadedb:26.4.1-SNAPSHOT"]- ChatGPT: ChatGPT connects only to remote servers that need no API key.
Recipes come from the server's entry in the official MCP registry. Check the package name before you run it, and keep keys out of shared files.
Works with
What ArcadeData/arcadedb connects to
5 clients, each with how we know and when we checked.
| Works with | Type | How we know | Checked |
|---|---|---|---|
| Claude Code | Client | Install recipe matches the client's documented formatRuns locally, version 26.4.1-SNAPSHOTConfig checked | Claude Code docs |
| Claude Desktop | Client | Install recipe matches the client's documented formatRuns locally, version 26.4.1-SNAPSHOTConfig checked | Claude Desktop docs |
| Cursor | Client | Install recipe matches the client's documented formatRuns locally, version 26.4.1-SNAPSHOTConfig checked | Cursor docs |
| VS Code | Client | Install recipe matches the client's documented formatRuns locally, version 26.4.1-SNAPSHOTConfig checked | VS Code docs |
| Codex | Client | Install recipe matches the client's documented formatRuns locally, version 26.4.1-SNAPSHOTConfig checked | Codex docs |
Health and security
Is ArcadeData/arcadedb looked after, and what do its setup files show
Health score
100 out of 100
| Part | Points | What we saw |
|---|---|---|
| Recent activity | 30 of 30 | Last push 0 days ago |
| Releases | 15 of 15 | 4 releases in 90 days |
| Issue replies | Not counted | The latest check has no issue response reading (fewer than 3 measured issues, or issues switched off) |
| Maintainer | 15 of 15 | Owned by an organisation |
| Official source | 20 of 20 | Official server |
Security check static checks
100 out of 100
- Note No published npm or PyPI package of this repository was found, so package advisories were not checked.
- Note The lab has not recorded this server's tool list yet, so tool permissions were not checked.
Alternatives
Alternatives to ArcadeData/arcadedb
| Record | Type | How we know | Checked |
|---|---|---|---|
| MilvusThis is an alternative to it | Open source | Named in the listing | Not dated |
| QdrantThis is an alternative to it | Open source | Named in the listing | Not dated |
Compare
Compare ArcadeData/arcadedb side by side
Sources
Where this comes from
- GitHubRegistry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
No changes recorded yet. Releases, price changes and deprecations appear here, with their dates, once we track them for this record.
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Milvus
Community
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Qdrant
Community
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
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