Knuckles-Team/vector-mcp
If you are the rightful owner of vector-mcp and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
Vector MCP Server for AI Agents - Supports ChromaDB, Couchbase, MongoDB, Qdrant, and PGVector
Vector Database MCP Server
Version: 0.1.9
This is an MCP Server implementation which allows for a standardized collection management system across vector database technologies.
This was heavily inspired by the RAG implementation of Microsoft's Autogen V1 framework, however, this was changed to an MCP server model instead.
AI Agents can:
- Create collections with documents stored on the local filesystem or URLs
- Add documents to a collection
- Utilize collection for retrieval augmented generation (RAG)
- Delete collection
Supports:
- ChromaDB
- PGVector - 90% Tested
- Couchbase - 80% Tested
- Qdrant - 80% Tested
- MongoDB - 80% Tested
This repository is actively maintained - Contributions and bug reports are welcome!
Automated tests are planned
Usage:
Using as an MCP Server:
Creating Collection
AI Prompt:
Create a collection called zapdos with the documents in this directory:
/home/user/Documents/Chroma
AI Response:
The collection named "zapdos" has been successfully created or retrieved from the vector database
using the documents in the directory /home/user/Documents/Chroma.
Let me know if you'd like to perform any further actions, such as querying the collection or adding more documents!
Retrieving from Collection
AI Prompt:
Create a collection called zapdos with the documents in this directory:
/home/user/Documents/Chroma
AI Response:
The collection named "zapdos" has been successfully created or retrieved from the vector database
using the documents in the directory /home/user/Documents/Chroma.
Let me know if you'd like to perform any further actions, such as querying the collection or adding more documents!
Deleting Collection
AI Prompt:
Delete the collection called memory
AI Response:
The collection named "memory" has been successfully deleted.
Let me know if you'd like to create a new collection or perform any other actions!
Example:
Use in CLI
Short Flag | Long Flag | Description |
---|---|---|
-h | --help | See Usage |
-h | --host | Host of Vector Database |
-p | --port | Port of Vector Database |
-d | --path | Path of local Vector Database |
-t | --transport | Transport Type (https/stdio) |
vector-mcp
Use with AI
Deploy MCP Server as a Service
docker pull knucklessg1/vector-mcp:latest
Modify the compose.yml
services:
vector-mcp-mcp:
image: knucklessg1/vector-mcp:latest
volumes:
- development:/root/Development
environment:
- HOST=0.0.0.0
- PORT=8001
ports:
- 8001:8001
Configure mcp.json
{
"mcpServers": {
"vector_mcp": {
"command": "uv",
"args": [
"run",
"--with",
"vector-mcp",
"vector-mcp"
],
"env": {
"DATABASE_TYPE": "chromadb", // Optional
"COLLECTION_NAME": "memory", // Optional
"DOCUMENT_DIRECTORY": "/home/user/Documents/" // Optional
},
"timeout": 300000
}
}
}
Installation Instructions:
Install Python Package
python -m pip install vector-mcp
PGVector dependencies
python -m pip install vector-mcp[pgvector]
All
python -m pip install vector-mcp[all]
Repository Owners:
Special shoutouts to Microsoft Autogen V1 ♥️