Rememberizer Vector Store MCP Server
Enables LLMs to interact with Rememberizer Vector Store for semantic search, document creation, deletion, and modification.
README
Rememberizer Vector Store MCP Server
A Model Context Protocol server for LLMs to interact with Rememberizer Vector Store.
Components
Resources
The server provides access to your Vector Store's documents in Rememberizer.
Tools
-
rememberizer_vectordb_search- Search for documents in your Vector Store by semantic similarity
- Input:
q(string): Up to a 400-word sentence to find semantically similar chunks of knowledgen(integer, optional): Number of similar documents to return (default: 5)
-
rememberizer_vectordb_agentic_search- Search for documents in your Vector Store by semantic similarity with LLM Agents augmentation
- Input:
query(string): Up to a 400-word sentence to find semantically similar chunks of knowledge. This query can be augmented by our LLM Agents for better results.n_chunks(integer, optional): Number of similar documents to return (default: 5)user_context(string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared results (default: None)
-
rememberizer_vectordb_list_documents- Retrieves a paginated list of all documents
- Input:
page(integer, optional): Page number for pagination, starts at 1 (default: 1)page_size(integer, optional): Number of documents per page, range 1-1000 (default: 100)
- Returns: List of documents
-
rememberizer_vectordb_information- Get information of your Vector Store
- Input: None required
- Returns: Vector Store information details
-
rememberizer_vectordb_create_document- Create a new document for your Vector Store
- Input:
text(string): The content of the documentdocument_name(integer, optional): A name for the document
-
rememberizer_vectordb_delete_document- Delete a document from your Vector Store
- Input:
document_id(integer): The ID of the document you want to delete
-
rememberizer_vectordb_modify_document- Change the name of your Vector Store document
- Input:
document_id(integer): The ID of the document you want to modify
Installation
Manual Installation: Use uvx command to install the Rememberizer Vector Store MCP Server.
uvx mcp-rememberizer-vectordb
Via MseeP AI Helper App: If you have MseeP AI Helper app installed, you can search for "Rememberizer VectorDb" and install the mcp-rememberizer-vectordb.

Configuration
Environment Variables
The following environment variables are required:
REMEMBERIZER_VECTOR_STORE_API_KEY: Your Rememberizer Vector Store API token
You can register an API key by create your own Vector Store in Rememberizer.
Usage with Claude Desktop
Add this to your claude_desktop_config.json:
"mcpServers": {
"rememberizer": {
"command": "uvx",
"args": ["mcp-rememberizer-vectordb"],
"env": {
"REMEMBERIZER_VECTOR_STORE_API_KEY": "your_rememberizer_api_token"
}
},
}
Usage with MseeP AI Helper App
Add the env REMEMBERIZER_VECTOR_STORE_API_KEY to mcp-rememberizer-vectordb.

License
This MCP server is licensed under the Apache License 2.0.
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